
MCP-openproject
MCP-openproject
README
MCP Server for OpenProject with Netlify Express
View the deployed MCP function endpoint: https://gilded-fudge-69ca2e.netlify.app/mcp (Note: This endpoint is intended for MCP clients, not direct browser access).
About this MCP Server
This project provides a Model Context Protocol (MCP) server, built with Express and deployed as a Netlify Function. It allows AI agents (like Langflow agents, Claude, Cursor, etc.) to interact with a self-hosted OpenProject instance via defined tools.
This example demonstrates:
-
Setting up an MCP server using
@modelcontextprotocol/sdk
. -
Integrating with an external API (OpenProject).
-
Deploying the MCP server serverlessly using Netlify Functions.
-
Handling environment variables securely in Netlify.
-
Providing a bridge for remote SSE clients (like cloud-hosted Langflow) to connect to the stateless Netlify function via
mcp-proxy
andngrok
.
Implemented OpenProject Tools
The server exposes the following tools for interacting with OpenProject:
- Projects:
openproject-create-project
: Creates a new project.openproject-get-project
: Retrieves a specific project by ID.openproject-list-projects
: Lists all projects (supports pagination).openproject-update-project
: Updates an existing project's details.openproject-delete-project
: Deletes a project.
- Tasks (Work Packages):
openproject-create-task
: Creates a new task within a project.openproject-get-task
: Retrieves a specific task by ID.openproject-list-tasks
: Lists tasks, optionally filtered by project ID (supports pagination).openproject-update-task
: Updates an existing task (requireslockVersion
).openproject-delete-task
: Deletes a task.
Prerequisites
- Node.js (v18 or later recommended)
- npm
- Netlify CLI (
npm install -g netlify-cli
) - Python 3.10 or later (required for the
mcp-proxy
tool used for SSE bridging) pip
(Python package installer)- An OpenProject instance accessible via URL.
- An OpenProject API Key.
- (Optional)
ngrok
account and CLI for testing remote SSE clients.
Setup Instructions
-
Clone the repository:
git clone git@github.com:jessebautista/mcp-openproject.git cd mcp-openproject
-
Install Node.js dependencies:
npm install
-
Install Python
mcp-proxy
: (Ensure you have Python 3.10+ active)# Check your python version first if needed: python3 --version # Install mcp-proxy (using pip associated with Python 3.10+): python3.10 -m pip install mcp-proxy # Or python3.11, python3.12 etc. depending on your version # If pipx is installed and preferred: pipx install mcp-proxy
Local Development
-
Create Environment File:
- Create a file named
.env
in the project root. - Add your OpenProject details:
OPENPROJECT_API_KEY="your_openproject_api_key_here" OPENPROJECT_URL="https://your_openproject_instance.com" OPENPROJECT_API_VERSION="v3"
- (Important): Ensure
.env
is listed in your.gitignore
file to avoid committing secrets.
- Create a file named
-
Run Netlify Dev Server:
- This command starts a local server, loads variables from
.env
, and makes your function available.
netlify dev
- Your local MCP endpoint will typically be available at
http://localhost:8888/mcp
.
- This command starts a local server, loads variables from
-
Test Locally with MCP Inspector:
- In a separate terminal, run the MCP Inspector, pointing it to your local server via
mcp-remote
:
npx @modelcontextprotocol/inspector npx mcp-remote@next http://localhost:8888/mcp
- Open the Inspector URL (usually
http://localhost:6274
) in your browser. - Connect and use the "Tools" tab to test the OpenProject CRUD operations.
- In a separate terminal, run the MCP Inspector, pointing it to your local server via
Deployment to Netlify
-
Set Environment Variables in Netlify UI:
- Go to your site's dashboard on Netlify (
https://app.netlify.com/sites/gilded-fudge-69ca2e/configuration/env
). - Under "Environment variables", add the following variables (ensure they are available to "Functions"):
OPENPROJECT_API_KEY
: Your OpenProject API key.OPENPROJECT_URL
: Your OpenProject instance URL (e.g.,https://project.bautistavirtualrockstars.com
).OPENPROJECT_API_VERSION
:v3
- (Security): The code in
netlify/mcp-server/index.ts
reads these fromprocess.env
. The hardcoded values should be removed (already done in our steps).
- Go to your site's dashboard on Netlify (
-
Deploy via Git:
- Commit your code changes:
git add . git commit -m "Deploy OpenProject MCP server updates"
- Push to the branch Netlify is configured to deploy (e.g.,
main
):
git push origin main
- Netlify will automatically build and deploy the new version. Monitor progress in the "Deploys" section of your Netlify dashboard.
Testing Deployed Version
-
Using MCP Inspector:
- Run the inspector, pointing
mcp-remote
to your live Netlify function URL:
npx @modelcontextprotocol/inspector npx mcp-remote@next https://gilded-fudge-69ca2e.netlify.app/mcp
- Open the Inspector URL and test the tools. Check Netlify function logs if errors occur.
- Run the inspector, pointing
-
Connecting Remote SSE Clients (e.g., Cloud-Hosted Langflow):
-
Since the Netlify function is stateless (doesn't handle SSE connections directly via GET), and remote clients like Langflow often prefer SSE, you need a bridge. We use the Python
mcp-proxy
tool combined with the JSmcp-remote
tool, andngrok
for a public tunnel. -
Step A: Start the Proxy Bridge Locally:
- Run this command in a terminal on your local machine (ensure Python 3.10+ is active and
mcp-proxy
is installed):
# Listen for SSE on local port 7865, run npx mcp-remote as the backend mcp-proxy --sse-port 7865 -- npx mcp-remote@next https://gilded-fudge-69ca2e.netlify.app/mcp
- Keep this terminal running. Check its output to ensure it started listening and spawned the
npx
command.
- Run this command in a terminal on your local machine (ensure Python 3.10+ is active and
-
Step B: Create a Public Tunnel with
ngrok
:- In a separate terminal, run
ngrok
to expose the local portmcp-proxy
is listening on:
ngrok http 7865
ngrok
will display a public "Forwarding" URL (e.g.,https://<random-string>.ngrok-free.app
). Copy this HTTPS URL.
- In a separate terminal, run
-
Step C: Configure Langflow:
- In your Langflow MCP Connection component (running on
https://lang.singforhope.org/
):- Mode:
SSE
- MCP SSE URL: Paste the full
ngrok
public URL including the/sse
path required bymcp-proxy
(e.g.,https://<random-string>.ngrok-free.app/sse
).
- Mode:
- Langflow should now be able to connect and use the tools via the
ngrok
->mcp-proxy
->mcp-remote
-> Netlify chain.
- In your Langflow MCP Connection component (running on
-
(Note): This
ngrok
setup is for testing/development. For a permanent solution, deploy themcp-proxy
bridge to a persistent public server.
-
Netlify Function Configuration (netlify.toml
)
Ensure your netlify.toml
correctly redirects requests to the /mcp
path to your Express function handler:
[[redirects]]
force = true
from = "/mcp/*" # Use wildcard to catch all sub-paths if needed
status = 200
to = "/.netlify/functions/express-mcp-server"
[[redirects]] # Also redirect the base path
force = true
from = "/mcp"
status = 200
to = "/.netlify/functions/express-mcp-server"
(Adjust redirects as needed based on your Express routing)
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.