Custom & internal agent frameworks

Your agents don't have to be Claude Code or Cursor for this to work

Plenty of engineering orgs run agents nobody else does — an internal framework built on top of an LLM API, a fork of an open-source agent loop, a home-grown orchestrator that predates LangGraph or Agent Framework entirely. threadctx doesn't care. It's a standard MCP server: any client that speaks MCP over stdio or HTTP can call its two tools, whether that client is Claude Code or something your own team wrote last year.

If your agent can be an MCP client, it already works

  • MCP is a wire protocol, not a framework lock-in. Most in-house agent stacks are built around a plain LLM API call loop. Adding MCP support to a loop like that is typically a small, self-contained client — the same effort as adding any other tool-calling capability, and something a growing number of internal frameworks already have, given how many public frameworks (Claude Code, Cursor, LangGraph, Microsoft Agent Framework) ship one already.
  • The config shape doesn't change. Every MCP client we've seen — public or internal — ultimately needs the same three things: a command to launch the server, its arguments, and an environment block for credentials. That's it.
  • We'll help with the rest. If your setup is unusual enough that wiring in an MCP client isn't obvious — a proprietary transport, an internal gateway that mediates tool calls, a compliance requirement around how credentials get passed — email founders@threadctx.dev and we'll work through it with you. Custom integration support is available for Team plan customers who need it.

The config, if you need a starting point

This is the exact block Claude Code and Cursor use. If your internal client reads config the same way (command + args + env), this is very likely all you need.

mcp.json
{
  "mcpServers": {
    "threadctx": {
      "command": "npx",
      "args": ["-y", "threadctx-mcp"],
      "env": {
        "THREADCTX_MODE": "cloud",
        "THREADCTX_API_KEY": "tctx_..."
      }
    }
  }
}

Two tools once connected: memory_write(content, tags?) and memory_query(task_description, max_results?). See what an MCP server is if your team is new to the protocol.

Talk to us about your setup.

Whatever your agents are built on, we want to help you get shared memory working — tell us what you're running.