Communication
mcp
by com.teamwork · v1.23.0
The Teamwork.com official MCP server helps teams efficiently manage client projects with AI.
- GitHub stars
- 22
- Transport
- stdio (local process)
- Auth
- None required
- Test status
- untested
Install & run
Run the server locally with the package command below.
terminal
$docker run -i --rm docker.io/teamwork/mcp:v1.23.0oci
docker.io/teamwork/mcp:v1.23.0· stdiosse
https://mcp.ai.teamwork.com/ssehttp
https://mcp.ai.teamwork.comConnect this MCP server to your AI agent
MCP servers plug into any MCP-compatible client (Claude Desktop, Cursor, your own agent runtime, and more). The steps are the same everywhere:
- 1. Make sure the runtime is available. This server runs as a local process, so its package runner (e.g. npx / uvx / docker) must be installed on the machine running your agent.
- 2. Add it to your MCP client config. Point your client at the command above. Most clients accept an MCP servers map keyed by a name of your choosing.
- 3. No credentials needed. This server declares no required secrets — it should work out of the box.
- 4. Restart your client and verify.The server’s tools should appear in your agent’s tool list, ready to call.
Want this running without wiring configs yourself? Run this with Alfe →
Communicationociremote
Data from the official MCP registry · last updated 2026-06-26 · ★ 22 stars via GitHub.