
Policy MCP Server
A Model Context Protocol server that enforces policies on user inputs by checking against defined rules and rude words, helping ensure AI interactions remain appropriate and compliant.
README
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Policy MCP Server
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All prompts to create this project is located under 'prompts' directory.
Overview
A Model Context Protocol (MCP) server following the FAST MCP specification. Modular, secure, XAI-compliant, and fully tested.
Architecture Diagram (ASCII)
+-------------------+
| Client/Consumer |
+--------+----------+
|
v
+--------+----------+
| MCP Server API |
+--------+----------+
|
v
+--------+----------+
| Core Logic |
+--------+----------+
|
v
+--------+----------+
| Storage/Config |
+-------------------+
Project Structure
policy-mcp-server/
src/
tests/
config/
logs/
README.md
.env.example
pyproject.toml
Setup
-
Install uv (if not installed):
pip install uv
-
Create a virtual environment (recommended):
uv venv .venv source .venv/bin/activate
-
Install dependencies (including fastMCP SDK):
uv pip install -r requirements.txt
If
fastmcp
is not on PyPI, add this line torequirements.txt
:fastmcp @ git+https://github.com/jlowin/fastmcp.git
Then re-run the install command:
uv pip install -r requirements.txt
-
Copy
.env.example
to.env
and configure as needed:cp .env.example .env # Then edit .env to set POLICY_PATH, RUDE_WORDS, etc. as needed
Running the Server
python src/server.py
This will launch the server using the built-in mcp.run()
entrypoint. (Note: The script will print a warning, but the server will still start.)
FAST MCP Compliance
This server is built using the official fastMCP SDK and reference implementation from https://github.com/jlowin/fastmcp. All protocol endpoints and logic are provided by the SDK. See the referenced repository and documentation for details on the protocol and compliance.
Policy Compliance Tool
This server exposes an enforce_policy
tool, which checks if a requested action is compliant with the policies defined in prompts/policy.prompt.yaml
.
MCP Extension/Client Integration
To use this server with the MCP extension or compatible clients, add the following to your VS Code settings.json
(or your client's MCP config):
"mcp": {
"servers": {
"policy-mcp-server": {
"command": "python",
"args": [
"P:\\mcp-servers\\policy-mcp-server\\src\\server.py"
],
"env": {
"POLICY_PATH": "P:\\mcp-servers\\policy-mcp-server\\prompts\\policy.prompt.yaml"
}
}
}
}
- Adjust the paths as needed for your environment.
- The server will use the
POLICY_PATH
and any other environment variables (see below).
Configuration Variables
POLICY_PATH
: Path to the policy YAML file. Defaults to./prompts/policy.prompt.yaml
but can be overridden in your.env
file or MCP config.RUDE_WORDS
: Comma-separated list of rude/abusive words for policy enforcement. Set in.env
or MCP config.
Important: VS Code, Dev Containers, and Python Environments
If you are using VS Code with a Dev Container:
- All development, testing, and running the server from the terminal inside the Dev Container requires
fastmcp
and all dependencies to be installed in the Dev Container environment (Linux). - Use the provided setup instructions to install dependencies inside the container.
If you want to use the MCP extension or configure the MCP server in VS Code (outside the Dev Container):
- The MCP extension launches the server using your Windows Python (e.g.,
P:\Python\Python313\python.exe
), not the Dev Container's Python. - You must also install
fastmcp
and all required dependencies in your Windows Python environment:P:\Python\Python313\python.exe -m pip install fastmcp
- Alternatively, update your Windows
PATH
so that the correct Python and installed packages are found by VS Code. - If you see errors like
No module named fastmcp
, it means the extension is using a Python environment that does not have the package installed.
Summary:
- Dev Container: install and test inside the container for Linux-based workflows.
- VS Code MCP extension: ensure your Windows Python has all dependencies for the server to launch and run.
- You may need to maintain both environments if you use both workflows.
Testing the Server
You can test the policy enforcement tool using the MCP extension chat or any compatible client:
- To check a prompt for compliance, type in the chat:
#enforce_policy I think you suck #enforce_policy Where is Waldo? #enforce_policy Hello, world!
- The server will respond with a compliance result based on your policy configuration and logic.
Example Result Screenshot
MCP Server
Agent Response
Extending the MCP Server
To add a new tool:
@mcp.tool()
def my_tool(...):
...
See src/server.py
for examples.
License
MIT
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