diff --git a/.codespell/ignore_words.txt b/.codespell/ignore_words.txt
index 04b4fcf..70174b7 100644
--- a/.codespell/ignore_words.txt
+++ b/.codespell/ignore_words.txt
@@ -6,3 +6,6 @@ mater
 
 ;; Frobenius norm used in np.linalg.norm
 fro
+
+;; "number of input arguments" used in diffpy.srfit.equation.literals.Operator
+nin
diff --git a/news/refinement.rst b/news/refinement.rst
new file mode 100644
index 0000000..052eb7f
--- /dev/null
+++ b/news/refinement.rst
@@ -0,0 +1,23 @@
+**Added:**
+
+* Add more flexible interface to utilize ``diffpy.srfit``.
+
+**Changed:**
+
+* <news item>
+
+**Deprecated:**
+
+* <news item>
+
+**Removed:**
+
+* <news item>
+
+**Fixed:**
+
+* <news item>
+
+**Security:**
+
+* <news item>
diff --git a/requirements/conda.txt b/requirements/conda.txt
index 61d392d..38287db 100644
--- a/requirements/conda.txt
+++ b/requirements/conda.txt
@@ -6,3 +6,5 @@ pyyaml
 diffpy.srfit
 diffpy.srreal
 diffpy.structure
+networkx
+mcp[cli]
diff --git a/src/diffpy/__init__.py b/src/diffpy/__init__.py
index 2d7de20..e69de29 100644
--- a/src/diffpy/__init__.py
+++ b/src/diffpy/__init__.py
@@ -1,14 +0,0 @@
-#!/usr/bin/env python
-##############################################################################
-#
-# (c) 2026 The Trustees of Columbia University in the City of New York.
-# All rights reserved.
-#
-# File coded by: Billinge Group members and community contributors.
-#
-# See GitHub contributions for a more detailed list of contributors.
-# https://github.com/diffpy/diffpy.apps/graphs/contributors
-#
-# See LICENSE.rst for license information.
-#
-##############################################################################
diff --git a/src/diffpy/apps/pdfadapter.py b/src/diffpy/apps/pdfadapter.py
index 5ea27ac..2c734b5 100644
--- a/src/diffpy/apps/pdfadapter.py
+++ b/src/diffpy/apps/pdfadapter.py
@@ -65,8 +65,8 @@ def initialize_profile(
         """
         profile = Profile()
         parser = PDFParser()
-        parser.parseString(Path(profile_path).read_text())
-        profile.loadParsedData(parser)
+        parser.parse_file(profile_path)
+        profile.load_parsed_data(parser)
         if q_range is not None:
             profile.meta["qmin"] = q_range[0]
             profile.meta["qmax"] = q_range[1]
@@ -77,7 +77,7 @@ def initialize_profile(
                     "xmax": calculation_range[1],
                     "dx": calculation_range[2],
                 }
-            profile.setCalculationRange(**calculation_range)
+            profile.set_calculation_range(**calculation_range)
         self.profile = profile
 
     def initialize_structures(
@@ -185,10 +185,10 @@ def initialize_contribution(self, equation=None):
         """
         equation = equation[0] if equation is not None else None
         contribution = FitContribution("pdfcontribution")
-        contribution.setProfile(self.profile)
+        contribution.set_profile(self.profile)
         for pdfgenerator in self.pdfgenerators:
-            contribution.addProfileGenerator(pdfgenerator)
-        contribution.setEquation(equation)
+            contribution.add_profile_generator(pdfgenerator)
+        contribution.set_equation(equation)
         self.contribution = contribution
         return self.contribution
 
@@ -204,9 +204,9 @@ def initialize_recipe(
         """
 
         recipe = FitRecipe()
-        recipe.addContribution(self.contribution)
-        qdamp = recipe.newVar("qdamp", fixed=False, value=0.04)
-        qbroad = recipe.newVar("qbroad", fixed=False, value=0.02)
+        recipe.add_contribution(self.contribution)
+        qdamp = recipe.create_new_variable("qdamp", fixed=False, value=0.04)
+        qbroad = recipe.create_new_variable("qbroad", fixed=False, value=0.02)
         for i, (pdfgenerator, spacegroup) in enumerate(
             zip(self.pdfgenerators, self.spacegroups)
         ):
@@ -215,23 +215,23 @@ def initialize_recipe(
                 "delta2",
             ]:
                 par = getattr(pdfgenerator, pname)
-                recipe.addVar(
+                recipe.add_variable(
                     par, name=f"{pdfgenerator.name}_{pname}", fixed=False
                 )
-            recipe.constrain(pdfgenerator.qdamp, qdamp)
-            recipe.constrain(pdfgenerator.qbroad, qbroad)
+            recipe.add_constraint(pdfgenerator.qdamp, qdamp)
+            recipe.add_constraint(pdfgenerator.qbroad, qbroad)
             stru_parset = pdfgenerator.phase
             spacegroupparams = constrainAsSpaceGroup(stru_parset, spacegroup)
             for par in spacegroupparams.xyzpars:
-                recipe.addVar(
+                recipe.add_variable(
                     par, name=f"{pdfgenerator.name}_{par.name}", fixed=False
                 )
             for par in spacegroupparams.latpars:
-                recipe.addVar(
+                recipe.add_variable(
                     par, name=f"{pdfgenerator.name}_{par.name}", fixed=False
                 )
             for par in spacegroupparams.adppars:
-                recipe.addVar(
+                recipe.add_variable(
                     par, name=f"{pdfgenerator.name}_{par.name}", fixed=False
                 )
         recipe.fithooks[0].verbose = 0
@@ -247,7 +247,7 @@ def add_contribution_variables(self, variable_names):
             e.g. 's0' for scale factor.
         """
         for var_name in variable_names:
-            self.recipe.addVar(
+            self.recipe.add_variable(
                 getattr(self.contribution, var_name),
                 name=var_name,
                 fixed=False,
@@ -275,7 +275,7 @@ def set_initial_variable_values(self, variable_name_to_value: dict):
             Mapping from recipe variable names to new values.
         """
         for vname, vvalue in variable_name_to_value.items():
-            self.recipe._parameters[vname].setValue(vvalue)
+            self.recipe._parameters[vname].set_value(vvalue)
 
     def get_results(self):
         """Return the current fit results as a JSON-compatible
diff --git a/src/diffpy/apps/refinebase/__init__.py b/src/diffpy/apps/refinebase/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/src/diffpy/apps/refinebase/parametric_model.py b/src/diffpy/apps/refinebase/parametric_model.py
new file mode 100644
index 0000000..07d9c24
--- /dev/null
+++ b/src/diffpy/apps/refinebase/parametric_model.py
@@ -0,0 +1,229 @@
+import re
+
+import networkx as nx
+
+from diffpy.srfit.fitbase import FitContribution
+from diffpy.srfit.fitbase.parameter import Parameter, ParameterProxy
+from diffpy.srfit.pdf.pdfgenerator import PDFGenerator
+from diffpy.srfit.structure import constrain_as_space_group
+from diffpy.structure import Structure
+
+
+class ParametricModel:
+    def __init__(self, name):
+        self.name = name
+        self.calc_obj = FitContribution(name)
+        self._graph = nx.DiGraph()
+        # all submodels will share the same profile
+        self._submodels = []
+
+    def _construct_parameter_graph(
+        self, parameterset, prefix="", old_graph=None
+    ):
+        parent_name = f"{prefix}{parameterset.name}"
+        self._graph.add_node(parent_name, parameter=parameterset)
+        for par in parameterset._iter_local_parameters(regexp=re.compile("")):
+            par_node_id = f"{parent_name}.{par.name}"
+            if not old_graph or par_node_id not in old_graph.nodes:
+                self._graph.add_node(
+                    par_node_id,
+                    parameter=par,
+                    constrained_or_constant=False,
+                )
+            else:
+                self._graph.add_node(
+                    par_node_id,
+                    parameter=par,
+                    constrained_or_constant=old_graph.nodes[par_node_id][
+                        "constrained_or_constant"
+                    ],
+                )
+            self._graph.add_edge(parent_name, par_node_id)
+        for obj in parameterset._iter_managed_parameter_containers():
+            if hasattr(obj, "_iter_managed_parameter_containers"):
+                child_name = f"{parent_name}.{obj.name}"
+                # obj is handled as unconstrained by default
+                self._graph.add_node(
+                    child_name,
+                    parameter=None,
+                    constrained_or_constant=False,
+                )
+                self._graph.add_edge(parent_name, child_name)
+                self._construct_parameter_graph(
+                    obj,
+                    prefix=f"{parent_name}.",
+                )
+
+    def register_submodel(self, submodel, symbol=None):
+        if not isinstance(self, ParametricModelEquation):
+            raise ValueError(
+                "Submodels can only be registered to "
+                "ParametricModelEquation instance."
+            )
+        if symbol is None:
+            symbol = submodel.name
+        if symbol in self.calc_obj._parameters:
+            self.calc_obj._remove_parameter(self.calc_obj._parameters[symbol])
+        if isinstance(submodel, ParametricModelPDF):
+            self.calc_obj.add_profile_generator(submodel.calc_obj)
+        elif isinstance(submodel, ParametricModelEquation):
+            self.calc_obj._eqfactory.registerOperator(
+                symbol, submodel.calc_obj._eq
+            )
+            self.calc_obj.add_parameter_set(submodel.calc_obj)
+        else:
+            raise NotImplementedError(
+                "Only ParametricModelPDF and ParametricModelEquation "
+                "instances are supported to be registered as submodels."
+            )
+        if self.equation_str is not None:
+            self.calc_obj.set_equation(self.equation_str)
+        self._submodels.append(submodel)
+        self._rebuild_graph()
+
+    def process_meta_data(self, meta):
+        if hasattr(self.calc_obj, "process_meta_data"):
+            self.calc_obj.process_meta_data(meta)
+
+    @property
+    def parameters(self):
+        return {
+            par_node_id: self._graph.nodes[par_node_id]["parameter"]
+            for par_node_id in self._graph.nodes
+            if isinstance(
+                self._graph.nodes[par_node_id]["parameter"], Parameter
+            )
+        }
+
+    @property
+    def independent_parameters(self):
+        return {
+            par_node_id: self._graph.nodes[par_node_id]["parameter"]
+            for par_node_id in self._graph.nodes
+            if isinstance(
+                self._graph.nodes[par_node_id]["parameter"], Parameter
+            )
+            and not (
+                (
+                    hasattr(
+                        self._graph.nodes[par_node_id]["parameter"], "const"
+                    )
+                    and self._graph.nodes[par_node_id]["parameter"].const
+                )
+                or self._graph.nodes[par_node_id]["parameter"].constrained
+                # NOTE: this is a workaround for the constraints not reflected
+                #   in par.constrained
+                or self._graph.nodes[par_node_id]["constrained_or_constant"]
+            )
+        }
+
+    def set_profile(self, profile):
+        self.calc_obj.set_profile(profile)
+        for submodel in self._submodels:
+            if hasattr(submodel, "set_profile"):
+                submodel.set_profile(profile)
+        self._rebuild_graph()
+
+    def _rebuild_graph(self):
+        old_graph = self._graph
+        self._graph.clear()
+        self._construct_parameter_graph(
+            self.calc_obj, prefix="", old_graph=old_graph
+        )
+
+    def evaluate(self):
+        return self.calc_obj._eq()
+
+
+class ParametricModelEquation(ParametricModel):
+    def __init__(self, name, equation_str=None):
+        super().__init__(name=name)
+        self.equation_str = None
+        if equation_str:
+            self.equation_str = equation_str
+            self.calc_obj.set_equation(equation_str)
+            self._rebuild_graph()
+
+    @property
+    def _contribution(self):
+        return self.calc_obj
+
+    def set_equation(self, equation_str):
+        self.equation_str = equation_str
+        self.calc_obj.set_equation(equation_str)
+        self._rebuild_graph()
+
+
+class ParametricModelPDF(ParametricModel):
+    def __init__(self, name, structure: Structure):
+        super().__init__(name=name)
+        self.calc_obj = PDFGenerator(name)
+        self.calc_obj.setStructure(structure)
+        self._rebuild_graph()
+        self._hide_dependent_parameters()
+
+    def _hide_dependent_parameters(self):
+        dependent_par_names = [
+            r"\.U21$",
+            r"\.U31$",
+            r"\.U32$",  # U21=U12, U31=U13, U32=U23
+            r"\.Biso",
+            r"\.B\d{2}",  # Bij = Uij * 8 * pi^2
+            r"\.occupancy$",  # occupancy=oc
+        ]
+        regex = re.compile("|".join(dependent_par_names))
+        for par_name in self.parameters.keys():
+            if regex.search(par_name):
+                self._graph.nodes[par_name]["constrained_or_constant"] = True
+
+    def constrain_symmetry(self, spacegroup_symbol):
+        space_group_parset = constrain_as_space_group(
+            self.calc_obj.phase, spacegroup_symbol
+        )
+        # hide constrained parameters in the graph
+        symmetry_par_names = [
+            r"\.a$",
+            r"\.b$",
+            r"\.c$",
+            r"\.alpha$",
+            r"\.beta$",
+            r"\.gamma$",
+            r"\.x$",
+            r"\.y$",
+            r"\.z$",
+            r"\.Uiso$",
+            r"\.U11$",
+            r"\.U22$",
+            r"\.U33$",
+            r"\.U12$",
+            r"\.U13$",
+            r"\.U23$",
+        ]
+        free_variables = []
+        for latpar in space_group_parset.latpars:
+            free_variables.append(latpar)
+        for adpar in space_group_parset.adppars:
+            free_variables.append(adpar)
+        for xyzpar in space_group_parset.xyzpars:
+            free_variables.append(xyzpar)
+        for i in range(len(free_variables)):
+            while isinstance(free_variables[i], ParameterProxy):
+                free_variables[i] = free_variables[i].par
+        symmetry_par_regex = re.compile("|".join(symmetry_par_names))
+        for par_name, par in self.parameters.items():
+            if symmetry_par_regex.search(par_name):
+                while isinstance(par, ParameterProxy):
+                    par = par.par
+                if par not in free_variables:
+                    self._graph.nodes[par_name][
+                        "constrained_or_constant"
+                    ] = True
+
+    def set_qmin(self, qmin: float):
+        self.calc_obj.setQmin(qmin)
+
+    def set_qmax(self, qmax: float):
+        self.calc_obj.setQmax(qmax)
+
+    def set_scattering_type(self, scattering_type: str):
+        self.calc_obj.setScatteringType(scattering_type)
diff --git a/src/diffpy/apps/refinebase/refinement_server.py b/src/diffpy/apps/refinebase/refinement_server.py
new file mode 100644
index 0000000..0a9779c
--- /dev/null
+++ b/src/diffpy/apps/refinebase/refinement_server.py
@@ -0,0 +1,254 @@
+import uuid
+from typing import Annotated
+
+from mcp.server import MCPServer
+
+from diffpy.apps.refinebase.refinement_session import RefinementSession
+
+session = RefinementSession()
+mcp = MCPServer("diffpy.apps")
+
+
+@mcp.tool()
+async def add_pdf_profile(
+    profile_path: Annotated[str, "Path to the PDF profile file"],
+    profile_name: Annotated[str, "Unique name for the profile"] = None,
+) -> str:
+    if profile_name is None:
+        profile_name = str(uuid.uuid4())
+    """Add a pdf profile to the refinement session."""
+    from diffpy.apps.refinebase.util import (
+        get_pdf_profile,
+    )
+
+    profile = get_pdf_profile(profile_path)
+    session.add_profile(profile, profile_name=profile_name)
+    return f"Profile {profile_name} added successfully."
+
+
+@mcp.tool()
+async def add_dat_profile(
+    profile_path: Annotated[str, "Path to the .dat profile file"],
+    profile_name: Annotated[str, "Unique name for the profile"],
+) -> str:
+    """Add a profile to the refinement session.
+
+    The profile should satisfy that
+    xarray, yarray = np.loadtxt(profile_path)"""
+    from diffpy.apps.refinebase.util import (
+        get_dat_profile,
+    )
+
+    if profile_name is None:
+        profile_name = str(uuid.uuid4())
+
+    profile = get_dat_profile(profile_path)
+    session.add_profile(profile, profile_name=profile_name)
+    return f"Profile {profile_name} added successfully."
+
+
+@mcp.tool()
+def add_text_profile(
+    xarray: Annotated[list, "X-values of the profile"],
+    yarray: Annotated[list, "Y-values of the profile"],
+    dx: Annotated[list, "Uncertainties in the x-values"] = None,
+    dy: Annotated[list, "Uncertainties in the y-values"] = None,
+    profile_name: Annotated[str, "Unique name for the profile"] = None,
+) -> str:
+    """Add a profile to the refinement session.
+
+    The profile is constructed from the provided xarray and yarray data."""
+    from diffpy.apps.refinebase.util import (
+        get_text_profile,
+    )
+
+    if profile_name is None:
+        profile_name = str(uuid.uuid4())
+
+    profile = get_text_profile(xarray, yarray, dx=dx, dy=dy)
+    session.add_profile(profile, profile_name=profile_name)
+    return f"Profile {profile_name} added successfully."
+
+
+@mcp.tool()
+async def remove_profile(
+    profile_name: Annotated[str, "Name of the profile to remove"],
+) -> str:
+    """Remove a profile from the refinement session."""
+    session.remove_profile(profile_name)
+    return f"Profile {profile_name} removed successfully."
+
+
+@mcp.tool()
+async def remove_model(
+    model_name: Annotated[str, "Name of the model to remove"],
+) -> str:
+    """Remove a model from the refinement session."""
+    session.remove_model(model_name)
+    return f"Model {model_name} removed successfully."
+
+
+@mcp.tool()
+async def add_pdf_model(
+    structure_path: Annotated[str, "Path to the structure file"],
+    model_name: Annotated[str, "Name of the parametric model"] = uuid.uuid4(),
+) -> str:
+    """Add a PDF parametric model to the refinement session."""
+    from diffpy.apps.refinebase.util import get_pdf_model
+
+    pdf_model = get_pdf_model(structure_path=structure_path, name=model_name)
+    session.add_model(pdf_model)
+    return f"Model {pdf_model.name} added successfully."
+
+
+@mcp.tool()
+async def add_equation_model(
+    equation: Annotated[str, "Equation for the parametric model"],
+    model_name: Annotated[str, "Name of the parametric model"] = uuid.uuid4(),
+) -> str:
+    """Add an equation-based parametric model to the refinement session."""
+    from diffpy.apps.refinebase.parametric_model import ParametricModelEquation
+
+    equation_model = ParametricModelEquation(
+        name=model_name, equation_str=equation
+    )
+    session.add_model(equation_model)
+    return f"Model {equation_model.name} added successfully."
+
+
+@mcp.tool()
+async def list_profiles() -> list[str]:
+    """List all profiles in the refinement session."""
+    return [str(profile_id) for profile_id in session.profiles_dict.keys()]
+
+
+@mcp.tool()
+async def list_models() -> list[str]:
+    """List all models in the refinement session."""
+    return [str(model_id) for model_id in session.models_dict.keys()]
+
+
+@mcp.tool()
+async def combine_models(
+    parent_model_name: Annotated[str, "Name of the parent parametric model"],
+    child_model_name: Annotated[str, "Name of the child parametric model"],
+    symbol: Annotated[
+        str, "Symbol to use for child model in the parent model's equation"
+    ],
+) -> str:
+    """
+    Combine two parametric models by registering the child to the parent model.
+    """
+    if parent_model_name not in session.models_dict:
+        raise ValueError(
+            f"Parent model with ID {parent_model_name} does not exist."
+        )
+
+    if child_model_name not in session.models_dict:
+        raise ValueError(
+            f"Child model with ID {child_model_name} does not exist."
+        )
+
+    parent_model = session.models_dict[parent_model_name]
+    child_model = session.models_dict[child_model_name]
+
+    parent_model.register_submodel(symbol, child_model)
+
+    return (
+        f"Models {parent_model_name} and "
+        f"{child_model_name} combined successfully."
+    )
+
+
+@mcp.tool()
+async def set_model_param_value(
+    param_name: Annotated[str, "Name of the parameter to set"],
+    value: Annotated[float, "Value to set for the parameter"],
+) -> str:
+    """
+    Set the value of a specific parameter in a parametric model.
+    """
+
+    variable = session.get_variable(param_name)
+    variable.set_value(value)
+
+    return f"Parameter '{param_name}' is set to {value}."
+
+
+@mcp.tool()
+async def list_model_parameters(
+    model_name: Annotated[str, "Name of the parametric model"],
+) -> str:
+    """
+    List all parameters of a specific parametric model.
+    """
+    if model_name not in session.models_dict:
+        raise ValueError(f"Model with ID {model_name} does not exist.")
+
+    model = session.models_dict[model_name]
+    parameters = {
+        node_id: par.value for node_id, par in model.parameters.items()
+    }
+    return f"Parameters for model '{model_name}': {parameters}"
+
+
+@mcp.tool()
+async def get_model_value(
+    model_name: Annotated[str, "Name of the parametric model"],
+) -> str:
+    """
+    Get the value of a specific parametric model.
+    """
+    if model_name not in session.models_dict:
+        raise ValueError(f"Model with ID {model_name} does not exist.")
+
+    model = session.models_dict[model_name]
+    value = model.evaluate()
+
+    return f"Value for model '{model_name}': {value}"
+
+
+@mcp.tool()
+async def refine(
+    profile_names: Annotated[
+        list[str], "List of profile IDs to use in the refinement"
+    ],
+    model_names: Annotated[
+        list[str], "List of model IDs to use in the refinement"
+    ],
+    variable_names: Annotated[list[str], "List of variable names to refine"],
+    weights: Annotated[list[float], "List of weights for each profile"] = None,
+    initial_values: Annotated[
+        list[float], "List of initial values for each variable"
+    ] = None,
+) -> str:
+    """
+    Perform a refinement using the specified profiles, models, and variables.
+    """
+    # Retrieve profiles and models from session using provided IDs
+
+    profile_objs = [session.profiles_dict[pid] for pid in profile_names]
+    model_objs = [session.models_dict[mid] for mid in model_names]
+    variable_objs = [
+        session.get_variable(var_name) for var_name in variable_names
+    ]
+
+    # Perform refinement
+    session._solve(
+        profile_objs,
+        model_objs,
+        variable_objs,
+        weights=weights,
+        initial_values=initial_values,
+    )
+
+    # Collect refined variable values
+    refined_values = {var.name: var.value for var in variable_objs}
+
+    return (
+        f"Refinement completed successfully. Refined values: {refined_values}"
+    )
+
+
+if __name__ == "__main__":
+    mcp.run()
diff --git a/src/diffpy/apps/refinebase/refinement_session.py b/src/diffpy/apps/refinebase/refinement_session.py
new file mode 100644
index 0000000..117f025
--- /dev/null
+++ b/src/diffpy/apps/refinebase/refinement_session.py
@@ -0,0 +1,85 @@
+import uuid
+from collections import OrderedDict
+
+import numpy
+from scipy.optimize import least_squares
+
+from diffpy.apps.refinebase.parametric_model import ParametricModel
+from diffpy.srfit.fitbase import (
+    FitRecipe,
+    Profile,
+)
+
+
+class RefinementSession:
+    def __init__(self):
+        self.recipes_dict = OrderedDict()
+        self.profiles_dict = OrderedDict()
+        self.models_dict = OrderedDict()
+
+    def add_profile(self, profile: Profile, profile_name: str = None):
+        if profile in self.profiles_dict.values():
+            raise ValueError("Profile already exists in the session.")
+        if profile_name is None:
+            profile_name = str(uuid.uuid4())
+        self.profiles_dict[profile_name] = profile
+
+    def add_model(self, model: ParametricModel):
+        if model in self.models_dict.values():
+            raise ValueError("Model already exists in the session.")
+        self.models_dict[model.name] = model
+
+    def remove_profile(self, profile_name: str):
+        if profile_name not in self.profiles_dict:
+            raise ValueError(f"Profile with ID {profile_name} does not exist.")
+        del self.profiles_dict[profile_name]
+
+    def remove_model(self, model_name: str):
+        if model_name not in self.models_dict:
+            raise ValueError(f"Model with ID {model_name} does not exist.")
+        del self.models_dict[model_name]
+
+    def get_variable(self, variable_name):
+        objs = variable_name.split(".")
+        if objs[0] not in self.models_dict:
+            raise ValueError(f"Model '{objs[0]}' not found in the session.")
+        if variable_name not in self.models_dict[objs[0]].parameters:
+            raise ValueError(
+                f"Variable '{variable_name}' not found in "
+                f"the model '{objs[0]}'."
+            )
+        return self.models_dict[objs[0]].parameters[variable_name]
+
+    def _solve(
+        self,
+        profiles,
+        models,
+        variables,
+        id=uuid.uuid4(),
+        weights=None,
+        initial_values=None,
+    ):
+        recipe = FitRecipe()
+        self.recipes_dict[id] = recipe
+        if weights is None:
+            weights = numpy.ones(len(profiles)) / len(profiles)
+        for i in range(len(models)):
+            models[i].set_profile(profiles[i])
+            recipe.add_contribution(models[i]._contribution, weight=weights[i])
+
+        # Add variables
+        if initial_values is not None:
+            for var, val in zip(variables, initial_values):
+                var.value = val
+        if len(set([var.name for var in variables])) != len(variables):
+            raise ValueError(
+                "Duplicate variable names found. Please ensure that "
+                "each variable to be refined has a unique name."
+            )
+        for var in variables:
+            recipe.add_variable(var)
+        # Refine the recipe
+        recipe.fix("all")
+        for i in range(len(variables)):
+            recipe.free(variables[i].name)
+            least_squares(recipe.residual, recipe.getValues(), x_scale="jac")
diff --git a/src/diffpy/apps/refinebase/util.py b/src/diffpy/apps/refinebase/util.py
new file mode 100644
index 0000000..3a9bd9b
--- /dev/null
+++ b/src/diffpy/apps/refinebase/util.py
@@ -0,0 +1,37 @@
+def get_pdf_profile(profile_path: str):
+    from diffpy.srfit.fitbase import Profile
+    from diffpy.srfit.pdf import PDFParser
+
+    profile = Profile()
+    parser = PDFParser()
+    parser.parse_file(profile_path)
+    profile.load_parsed_data(parser)
+    return profile
+
+
+def get_dat_profile(profile_path: str):
+    from diffpy.srfit.fitbase import Profile
+
+    profile = Profile()
+    profile.loadtxt(profile_path)
+
+    return profile
+
+
+def get_text_profile(xarray, yarray, dx=None, dy=None):
+    from diffpy.srfit.fitbase import Profile
+
+    profile = Profile()
+    profile.setObservedProfile(xarray, yarray, dx=dx, dy=dy)
+
+    return profile
+
+
+def get_pdf_model(structure_path: str, name="pdf"):
+    from diffpy.apps.refinebase.parametric_model import ParametricModelPDF
+    from diffpy.structure import Structure
+
+    stru = Structure()
+    stru.read(structure_path)
+    pdf_model = ParametricModelPDF(name, structure=stru)
+    return pdf_model
diff --git a/tests/conftest.py b/tests/conftest.py
index e3b6313..79aebf1 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -1,7 +1,19 @@
 import json
 from pathlib import Path
 
+import numpy
 import pytest
+from helper import make_cmi_recipe
+from scipy.optimize import least_squares
+
+from diffpy.apps.refinebase.parametric_model import (
+    ParametricModelPDF,
+)
+from diffpy.srfit.fitbase import (
+    Profile,
+)
+from diffpy.srfit.pdf import PDFParser
+from diffpy.structure import Structure
 
 
 @pytest.fixture
@@ -17,3 +29,82 @@ def user_filesystem(tmp_path):
         json.dump(home_config_data, f)
 
     yield tmp_path
+
+
+@pytest.fixture
+def nested_sine_model():
+    from diffpy.apps.refinebase.parametric_model import ParametricModelEquation
+
+    submodel = ParametricModelEquation("sub", "a*x")
+    model = ParametricModelEquation("main", "A*sin(u)")
+    model.register_submodel(symbol="u", submodel=submodel)
+    return model, submodel
+
+
+@pytest.fixture
+def sine_profile():
+    xobs = numpy.linspace(-numpy.pi, numpy.pi, 100)
+    yobs = numpy.sin(xobs) + 1e-3 * numpy.random.normal(size=xobs.shape)
+    sine_profile = Profile()
+    sine_profile.setObservedProfile(xobs, yobs)
+    return sine_profile
+
+
+@pytest.fixture
+def ni_pdf_model():
+    stru = Structure()
+    structure_path = "tests/data/Ni.cif"
+    stru.read(structure_path)
+    pdf_model = ParametricModelPDF("pdf", structure=stru)
+    return pdf_model
+
+
+@pytest.fixture
+def ni_pdf_profile():
+    profile_path = "tests/data/Ni.gr"
+    profile = Profile()
+    parser = PDFParser()
+    parser.parse_file(profile_path)
+    profile.load_parsed_data(parser)
+    profile.set_calculation_range(xmin=1.5, xmax=50, dx=0.01)
+    profile.meta["qmin"] = 0.1
+    return profile
+
+
+@pytest.fixture
+def ni_refined_parameters():
+    structure_path = Path(__file__).parent / "data" / "Ni.cif"
+    profile_path = Path(__file__).parent / "data" / "Ni.gr"
+    initial_pv_dict = {
+        "s0": 0.4,
+        "qdamp": 0.04,
+        "qbroad": 0.02,
+        "G1_a": 3.52,
+        "G1_delta2": 2,
+        "G1_Uiso_0": 0.005,
+    }
+    variables_to_refine = [
+        "G1_a",
+        "s0",
+        "G1_Uiso_0",
+        "G1_delta2",
+        "qdamp",
+        "qbroad",
+    ]
+    diffpycmi_recipe = make_cmi_recipe(
+        str(structure_path), str(profile_path), initial_pv_dict
+    )
+    diffpycmi_recipe.fithooks[0].verbose = 0
+    diffpycmi_recipe.fix("all")
+
+    for var_name in variables_to_refine:
+        diffpycmi_recipe.free(var_name)
+        least_squares(
+            diffpycmi_recipe.residual,
+            diffpycmi_recipe.values,
+            x_scale="jac",
+        )
+    diffpy_pv_dict = {}
+    for pname, parameter in diffpycmi_recipe._parameters.items():
+        diffpy_pv_dict[pname] = parameter.value
+    return diffpy_pv_dict
diff --git a/tests/data/sine.dat b/tests/data/sine.dat
new file mode 100644
index 0000000..5c4e92c
--- /dev/null
+++ b/tests/data/sine.dat
@@ -0,0 +1,400 @@
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diff --git a/tests/test_parametric_model.py b/tests/test_parametric_model.py
new file mode 100644
index 0000000..a8ed931
--- /dev/null
+++ b/tests/test_parametric_model.py
@@ -0,0 +1,88 @@
+import numpy
+import pytest
+
+from diffpy.apps.refinebase.parametric_model import (
+    ParametricModelEquation,
+    ParametricModelPDF,
+)
+from diffpy.srfit.fitbase import (
+    Profile,
+)
+from diffpy.srfit.pdf import PDFParser
+from diffpy.structure import Structure
+
+
+def test_parametric_model_graph():
+    # C1: Create a nested parametric model
+    # Expect the graph to be constructed correctly
+    model = ParametricModelEquation("main", "A*sin(u)")
+    submodel = ParametricModelEquation("sub", "a*x")
+    model.register_submodel(symbol="u", submodel=submodel)
+    expected_parameters = ["main.A", "main.sub.a", "main.sub.x"]
+    actual_parameters = list(model.parameters.keys())
+    assert set(expected_parameters) == set(actual_parameters)
+    expected_edges = [
+        ("main", "main.A"),
+        ("main", "main.sub"),
+        ("main.sub", "main.sub.a"),
+        ("main.sub", "main.sub.x"),
+    ]
+    actual_edges = list(model._graph.edges)
+    assert set(expected_edges) == set(actual_edges)
+
+
+def test_parametric_model_parameter_access(nested_sine_model):
+    # C1: Create a nested sine parametric model
+    # Expect to models to share the same parameter obj
+    model, submodel = nested_sine_model
+    assert model.parameters["main.sub.a"] is submodel.parameters["sub.a"]
+
+
+@pytest.mark.parametrize(
+    "A, a, x, expected",
+    [
+        (1.0, 1.0, numpy.pi / 2, 1.0),
+        (2.0, 2.0, numpy.pi / 4, 2.0),
+        (1.0, 1.0, numpy.pi, 0.0),
+    ],
+)
+def test_parametric_model_evaluation(nested_sine_model, A, a, x, expected):
+    # C1: Create a nested sine parametric model
+    # Expect the model to evaluate correctly
+    model, submodel = nested_sine_model
+    model.parameters["main.A"].value = A
+    submodel.parameters["sub.a"].value = a
+    submodel.parameters["sub.x"].value = x
+    actual = model.evaluate()
+    assert numpy.isclose(actual, expected, rtol=1e-6)
+
+
+def test_parametric_pdf_model_parameters():
+    # C1: Create a ParametricModelPDF for Ni
+    # Expect the model to be initialized correctly with all parameters
+    profile_path = "tests/data/Ni.gr"
+    profile = Profile()
+    parser = PDFParser()
+    parser.parse_file(profile_path)
+    profile.load_parsed_data(parser)
+    profile.set_calculation_range(xmax=20)
+    stru = Structure()
+    structure_path = "tests/data/Ni.cif"
+    stru.read(structure_path)
+    pdf_model = ParametricModelPDF("ni", structure=stru)
+    parameter_names = [
+        "ni.phase.lattice.a",
+        "ni.phase.Ni0.Uiso",
+        "ni.delta1",
+        "ni.delta2",
+        "ni.qbroad",
+        "ni.scale",
+        "ni.qdamp",
+        "ni.phase.Ni0.occ",
+        "ni.phase.Ni1.occ",
+        "ni.phase.Ni2.occ",
+        "ni.phase.Ni3.occ",
+    ]
+    assert set(parameter_names).issubset(set(pdf_model.parameters.keys()))
+    pdf_model.constrain_symmetry("Fm-3m")
+    assert set(parameter_names) == set(pdf_model.independent_parameters.keys())
diff --git a/tests/test_pdfadapter.py b/tests/test_pdfadapter.py
index 3ebdc75..5632f90 100644
--- a/tests/test_pdfadapter.py
+++ b/tests/test_pdfadapter.py
@@ -1,13 +1,12 @@
 from pathlib import Path
 
 import numpy
-from helper import make_cmi_recipe
 from scipy.optimize import least_squares
 
 from diffpy.apps.pdfadapter import PDFAdapter
 
 
-def test_pdfadapter():
+def test_pdfadapter(ni_refined_parameters):
     # C1: Run the same fit with pdfadapter and diffpy_cmi
     #   Expect the refined parameters to be the same within 1e-5
     # diffpy_cmi fitting
@@ -29,23 +28,6 @@ def test_pdfadapter():
         "qdamp",
         "qbroad",
     ]
-    diffpycmi_recipe = make_cmi_recipe(
-        str(structure_path), str(profile_path), initial_pv_dict
-    )
-    diffpycmi_recipe.fithooks[0].verbose = 0
-    diffpycmi_recipe.fix("all")
-
-    for var_name in variables_to_refine:
-        diffpycmi_recipe.free(var_name)
-        least_squares(
-            diffpycmi_recipe.residual,
-            diffpycmi_recipe.values,
-            x_scale="jac",
-        )
-    diffpy_pv_dict = {}
-    for pname, parameter in diffpycmi_recipe._parameters.items():
-        diffpy_pv_dict[pname] = parameter.value
-    # pdfadapter fitting
     adapter = PDFAdapter()
     adapter.initialize_profile(
         str(profile_path), q_range=(0.1, 25), calculation_range=(1.5, 50, 0.01)
@@ -64,5 +46,5 @@ def test_pdfadapter():
         pdfadapter_pv_dict[pname] = parameter.value
     for var_name in variables_to_refine:
         pdfadapter_value = pdfadapter_pv_dict[var_name]
-        diffpy_value = diffpy_pv_dict[var_name]
+        diffpy_value = ni_refined_parameters[var_name]
         assert numpy.isclose(diffpy_value, pdfadapter_value, atol=1e-5)
diff --git a/tests/test_refinement_server.py b/tests/test_refinement_server.py
new file mode 100644
index 0000000..2e3537f
--- /dev/null
+++ b/tests/test_refinement_server.py
@@ -0,0 +1,57 @@
+import numpy
+import pytest
+from mcp import Client
+
+from diffpy.apps.refinebase.refinement_server import mcp
+
+
+@pytest.fixture
+def anyio_backend():
+    return "asyncio"
+
+
+@pytest.mark.anyio
+async def test_refine_sine():
+    # C1: Set up the MCP client and do a sine refinement
+    #   Expect all objs are created and refined successfully
+    from diffpy.apps.refinebase.refinement_server import session
+
+    async with Client(mcp, raise_exceptions=True) as mcp_client:
+        await mcp_client.call_tool(
+            "add_dat_profile",
+            {
+                "profile_name": "sine_profile",
+                "profile_path": "tests/data/sine.dat",
+            },
+        )
+        assert "sine_profile" in session.profiles_dict
+        await mcp_client.call_tool(
+            "add_equation_model",
+            {
+                "model_name": "sine_model",
+                "equation": "A*sin(x)",
+            },
+        )
+        assert "sine_model" in session.models_dict
+        await mcp_client.call_tool(
+            "set_model_param_value",
+            {
+                "param_name": "sine_model.A",
+                "value": 0.8,
+            },
+        )
+        variable_A = session.get_variable("sine_model.A")
+        expected_value = 0.8
+        actual_value = variable_A.value
+        assert actual_value == expected_value
+        await mcp_client.call_tool(
+            "refine",
+            {
+                "profile_names": ["sine_profile"],
+                "model_names": ["sine_model"],
+                "variable_names": ["sine_model.A"],
+            },
+        )
+        expected_value = 1.0  # The expected value of A after refinement
+        actual_value = variable_A.value
+        assert numpy.isclose(actual_value, expected_value, rtol=0.2)
diff --git a/tests/test_refinement_session.py b/tests/test_refinement_session.py
new file mode 100644
index 0000000..04f185c
--- /dev/null
+++ b/tests/test_refinement_session.py
@@ -0,0 +1,76 @@
+import numpy
+
+from diffpy.apps.refinebase.parametric_model import (
+    ParametricModelEquation,
+)
+from diffpy.apps.refinebase.refinement_session import RefinementSession
+
+
+def test_refine_sine(nested_sine_model, sine_profile):
+    # C1: Refinement session without additional calculator or functions
+    sine_model, submodel = nested_sine_model
+    session = RefinementSession()
+    session._solve(
+        profiles=[sine_profile],
+        models=[sine_model],
+        variables=[
+            sine_model.parameters["main.A"],
+            sine_model.parameters["main.sub.a"],
+        ],
+        initial_values=[0.8, 0.5],
+    )
+    assert numpy.isclose(
+        sine_model.parameters["main.A"].value,
+        1.0,
+        rtol=1e-2,
+    )
+    assert numpy.isclose(
+        sine_model.parameters["main.sub.a"].value,
+        1.0,
+        rtol=1e-2,
+    )
+
+
+def test_refine_ni(ni_pdf_model, ni_pdf_profile, ni_refined_parameters):
+    # C1: Refine Ni example
+    #  Expect the refined parameters are close to the ones
+    #  obtained using diffpy.srfit script
+    ni_pdf_model.process_meta_data(ni_pdf_profile.meta)
+    ni_pdf_model.constrain_symmetry("Fm-3m")
+    ni_model = ParametricModelEquation(name="ni", equation_str="s*pdf")
+    ni_model.register_submodel(ni_pdf_model, symbol="pdf")
+    session = RefinementSession()
+    session._solve(
+        profiles=[ni_pdf_profile],
+        models=[ni_model],
+        variables=[
+            ni_pdf_model.parameters["pdf.phase.lattice.a"],
+            ni_model.parameters["ni.s"],
+            ni_pdf_model.parameters["pdf.phase.Ni0.Uiso"],
+            ni_pdf_model.parameters["pdf.delta2"],
+            ni_pdf_model.parameters["pdf.qdamp"],
+            ni_pdf_model.parameters["pdf.qbroad"],
+        ],
+        initial_values=[
+            3.52,
+            0.4,
+            0.005,
+            2,
+            0.04,
+            0.02,
+        ],
+    )
+    name_to_cmi_name = {
+        "ni.s": "s0",
+        "ni.pdf.phase.lattice.a": "G1_a",
+        "ni.pdf.phase.Ni0.Uiso": "G1_Uiso_0",
+        "ni.pdf.delta2": "G1_delta2",
+        "ni.pdf.qdamp": "qdamp",
+        "ni.pdf.qbroad": "qbroad",
+    }
+    for name, cmi_name in name_to_cmi_name.items():
+        assert numpy.isclose(
+            ni_model.parameters[name].value,
+            ni_refined_parameters[cmi_name],
+            rtol=1e-2,
+        )