Connect the AI apps you use and the systems you already have
Built on open standards (MCP and REST), so any AI app that speaks MCP can connect. Available now with Claude Code and Claude Desktop; ChatGPT, Gemini, Copilot, Cursor and others are in testing.
Where your people and agents connect from
| AI app or client | How it connects | Status |
|---|---|---|
| Claude Code | Verified today. Plugin and cmcp helper available. | Available now |
| Claude Desktop | Verified today. | Available now |
| Bots and digital workers | Connect with API keys. Each bot has its own identity and a human sponsor. | Available now |
| Your own applications | REST API described in OpenAPI 3.1. | Available now |
| ChatGPT, Gemini and Copilot | Any MCP- or REST-capable AI app can connect. Built and being validated. | In testing |
| Cursor, Codex, Gemini CLI and Cline | Coding tools connect through MCP or REST. Built and being validated. | In testing |
| Local models | Models you run yourselves can connect the same way. Built and being validated. | In testing |
| Claude on the web and mobile | Built and being validated. | In testing |
cMCP does not depend on one model or vendor. People are not forced onto one brand of laptop or email client, and your AI memory should not be locked to one model either. Change AI vendor, or use several at once; what your organisation has learned stays yours.
Built and in testing. Anything that does not pass testing will be removed.
Read-only connectors that never write back
Connectors read from outside systems and feed proposed facts into an approval queue. By design, cMCP never writes into outside systems.
| System | Behaviour | Status |
|---|---|---|
| Jira Cloud | Read-only. Proposed facts go to an approval queue. | Available now |
| PostgreSQL views | Read-only. Proposed facts go to an approval queue. | Available now |
| IMAP mailboxes | Read-only. Chosen folders only, with the sender domain verified. | Available now |
| Git repository addresses | Mapped to projects. The code itself is not read. | Available now |
| Microsoft 365 (mail, Teams, drives) | Built, and being connected and tested. | In testing |
| Google Drive | Built, and being connected and tested. | In testing |
| GitHub | Built, and being connected and tested. | In testing |
11 MCP tools and a REST API
AI apps use eleven MCP tools to fetch context, search, save, update, delete, refresh, request changes, check on requests, save session summaries and list the scopes they can see. A REST API, described in OpenAPI 3.1, covers everything else.
People sign in with OAuth 2.1, using a password plus an authenticator code. Access tokens are short-lived. Every call is permission-checked and recorded.
Available now
memory_get_context memory_search memory_save memory_update memory_delete memory_refresh memory_request_change memory_request_status memory_save_session_summary memory_list_scopes resource_lookup
Example MCP configuration
Illustrative only. The URL is a placeholder, and exact steps for your client are provided during the pilot.
{
"mcpServers": {
"cmcp": {
"type": "http",
"url": "https://your-cmcp-host/mcp"
}
}
}Tell us which AI apps and systems matter most
In the scoping workshop we agree which one or two systems and which AI apps to connect first.