Integrations

Every GraphMind adapter exposes the same shape, so the debugger works the same way whatever you write your agents in:

const gm = graphmind({ app: 'my-agent' });

gm.wrapClient(client);   // or gm.wrapModel(model) / gm.handler() for LangChain
gm.wrapTools({ ... });   // gates each tool call
gm.run(name, fn);        // one run, one AbortController, one agent node
await gm.ready();        // wait for the debugger handshake (optional, recommended)

What differs is only what each framework’s extension points allow — the LangGraph page has the honest matrix for the one case where a callback-only path cannot do everything.

One integration has no code surface at all. graphmind mcp-proxy sits between an MCP host and an MCP server and debugs the server without touching it — any language, including servers you did not write.

Adapters are built strictly on public extension points — middleware, callback handlers, client hooks, tool decoration. No forks, no monkey-patching of module internals, nothing that breaks on your framework’s next minor release.

Pick your stack

Vercel AI SDK@graphmind-ai/sdk — wrapLanguageModel middleware + tool execute decoration. The reference adapter.

Anthropic SDK@graphmind-ai/anthropic — wrap the client, gate messages.create and your tool loop.

OpenAI SDK@graphmind-ai/openai — wrap the client, gate responses / chat.completions and tools.

LangGraph & LangChain (JS)@graphmind-ai/langgraph — a callback handler that renders the run tree, plus gated tools.

MCP proxygraphmind mcp-proxy — debug an MCP server in any language, with no code changes at all.

MCP server (in-process)@graphmind-ai/mcp — wrap your TypeScript MCP server; gate every tool, resource, prompt and sampling call.

Pythongraphmind-ai on PyPI — openai, anthropic and langgraph, same protocol.

RubyThe graphmind gem — ruby-openai and RubyLLM, gated tools, and a Rails-shaped install.

Anything elseImport an OTel / OpenInference trace, or write an adapter against the wire schema.

What every adapter guarantees

Guarantee	Meaning
Never throws into your app	Internal failures degrade to a no-op plus one rate-limited warning
Identity when disabled	wrapClient / wrapTools return their input unchanged — zero overhead
Fast path when detached	Gates resolve from a shared promise; events go to the ring buffer only
Auto-continue on disconnect	Every held gate releases with continue
instanceId on every event	Correct attribution when the same node runs concurrently
Kill switches honoured	GRAPHMIND_DISABLED=1; off under NODE_ENV=production unless GRAPHMIND=1

Adapter maturity

@graphmind-ai/sdk (Vercel AI SDK) is the reference adapter and the most exercised. The Anthropic, OpenAI, LangGraph and Python adapters ship at the same version and cover the same surface, and each one has a real sample agent built against the published package. If you hit a gap, an issue is the fastest way to close it — the protocol is small enough that most gaps are a day of work.

Framework not listed?

Two paths, in increasing order of effort:

1. Import a trace you already produce. graphmind import trace.json accepts OTLP/JSON and flat OpenInference-style span lists and turns them into a run you can read in the viewer — history only, no live control. See other frameworks.
2. Write an adapter. The wire contract is nine event types over one WebSocket, and @graphmind-ai/client already owns the session, the gate engine and the fail-open logic. A working adapter is a few hundred lines. The guide walks the whole thing.