Twenty CRM REST/GraphQL MCP Server for Agentic AI!
Project description
Twenty MCP
Documentation — Installation, deployment, usage across the MCP, API, and agent interfaces, and guidance for provisioning the Twenty CRM platform are maintained in the official documentation.
Twenty CRM Customer Relationship Management system orchestrator. Built with the highest architectural standards, incorporating dynamic facades, custom API routing, and FastMCP tool decoration.
Table of Contents
- Overview
- Features
- Installation
- Usage
- Configuration
- MCP Tools
- Architecture
- Deployment
- Contributing
- License
Overview
Twenty MCP provides a high-performance, model-optimized interface to Twenty capabilities. It isolates the model from underlying API transport complexity, ensuring safe, idempotent, and highly traceable system interactions.
Features
- Dynamic Facade Orchestration: Integrates multi-inheritance clients cleanly under a single facade.
- Battle-Tested Resilience: Out-of-the-box credential authentication, connection polling, and request retry strategies.
- FastMCP Declarative Tools: Fast, native schema registration with full inline validation.
- Complete Test Intent Diversity: Deep, automated unit, integration, and mock tests ensuring high code coverage.
⚙️ Dynamic Tool Selection & Visibility
This MCP server supports dynamic toolset selection and visibility filtering at runtime. This allows you to restrict the set of exposed tools in order to prevent blowing up the LLM's context window.
You can configure tool filtering via multiple input channels:
- CLI Arguments: Pass
--toolsor--toolsets(or their disabled counterparts--disabled-toolsand--disabled-toolsets) during startup. - Environment Variables: Define standard environment variables:
MCP_ENABLED_TOOLS/MCP_DISABLED_TOOLSMCP_ENABLED_TAGS/MCP_DISABLED_TAGS
- HTTP SSE Request Headers: Pass custom headers during transport initialization:
x-mcp-enabled-tools/x-mcp-disabled-toolsx-mcp-enabled-tags/x-mcp-disabled-tags
- HTTP SSE Request Query Parameters: Append query parameters directly to your transport connection URL:
?tools=tool1,tool2?tags=tag1
When query strings or parameters are supplied, an LLM-free Knowledge Graph resolution layer (using DynamicToolOrchestrator) matches query intents against known tool tags, names, or descriptions, with safe fallback and automated 24-hour background cache refreshing.
Installation
Install in editable mode directly inside your active workspace:
pip install -e .[all]
Or via the uv tool:
uv pip install -e .
Usage
You can launch the FastMCP server in stdio mode via Python module execution:
import asyncio
from twenty_mcp.mcp_server import get_mcp_instance
async def main():
mcp = get_mcp_instance()
# Execute stdio loop or launch server
print("MCP Server ready.")
if __name__ == "__main__":
asyncio.run(main())
For direct shell launch, execute:
python -m twenty_mcp.mcp_server
Configuration
The package is fully configurable via the environment variables listed below:
| Variable | Description | Default | Required |
|---|---|---|---|
TWENTY_URL |
Twenty CRM Base Server URL | http://localhost:3000 |
Yes |
TWENTY_TOKEN |
Developer authentication token | twenty_developer_access_token |
Yes |
TWENTY_MCP_BASE_URL |
Base API URL to query | http://localhost:3000/api |
Yes |
TWENTY_MCP_USERNAME |
Auth username for service | admin |
Yes |
TWENTY_MCP_PASSWORD |
Auth password for service | secure_password |
Yes |
TWENTY_MCP_SSL_VERIFY |
SSL verification flag | True |
Yes |
CRMTOOL |
CRM Tool Enabled Flag | True |
Yes |
A local template is supplied inside .env.example. Copy this file as .env and fill out your specific service endpoint parameters before starting execution.
MCP Tools
The following declarative FastMCP tools are registered and available to upstream AI agents:
| Tool Name | Description | Parameters |
|---|---|---|
get_people |
Retrieve list of people in CRM | limit: int = 50 |
create_person |
Create a new person in CRM | first_name: str, last_name: str, email: str |
get_companies |
Retrieve list of companies in CRM | limit: int = 50 |
execute_gql |
Execute raw arbitrary GraphQL query | query: str, variables: dict = None |
See docs/overview.md or docs/concepts.md for deeper operational examples.
Architecture
This package uses the standardized Agent-Utilities dynamic facade architecture:
graph TD
User([User Agent]) --> Server[FastMCP Server]
Server --> Facade[Api Dynamic Facade]
Facade --> ClientBase[ApiClientBase]
Facade --> Auth[Credentials Auth Handler]
ClientBase --> Service([External Service API])
Deployment
Bare-Metal (Standard pip)
- Set up your Python virtual environment (>= 3.10).
- Install the package:
pip install .[all] - Export credentials:
export TWENTY_URL="http://localhost:3000"
- Run:
python -m twenty_mcp.mcp_server
Container (Docker Compose)
A standard compose structure is provided inside the docker/ folder. Build and deploy:
docker compose -f docker/compose.yml up --build -d
Additional Deployment Options
twenty-mcp can also run as a local container (Docker / Podman / uv) or be
consumed from a remote deployment. The
Deployment guide has full, copy-paste
mcp_config.json for all four transports — stdio, streamable-http,
local container / uv, and remote URL:
- Local container / uv — launch the server from
mcp_config.jsonviauvx,docker run, orpodman run, or point at a local streamable-http container byurl. - Remote URL — connect to a server deployed behind Caddy at
http://twenty-mcp.arpa/mcpusing the"url"key.
Documentation
The complete documentation is published as the official documentation site and is the recommended reference for installation, deployment, and day-to-day operation.
| Page | Contents |
|---|---|
| Installation | pip, source, extras, prebuilt Docker image |
| Deployment | run the MCP and agent servers, Compose, Caddy + Technitium, env config |
| Usage | the MCP tools, the Api client, the A2A agent |
| Backing Platform | deploy Twenty CRM with Docker |
| Overview | the dynamic facade architecture |
| Concepts | concept registry (CONCEPT:TWENTY-*) |
Contributing
Please audit all code changes against ecosystem guidelines in CONTRIBUTING.md if available, and run:
pre-commit run --all-files
License
This project is licensed under the MIT License. See the LICENSE file for complete details.
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