Llmgraph

io.github.abahocodesPublished by GitHub account abahocodesv0.1.1Updated Oct 24, 2026

Invoke deployed LLMGraph no-code LLM workflows (chat, RAG, automations) as MCP tools.

VerifiedSTDIODesktop onlyProductivity & Workflow AI & ML

Server details

Identifier: io.github.abahocodes/llmgraph
Transport: STDIO
Runtime: Desktop only
Trust: Verified
Published: Sep 16, 2026

Security note

MCP servers receive tool arguments from a conversation and may perform external actions. Review what a server can do before you enable it, and give it only the access it needs.

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Overview

AI-generated overview

Exposes your deployed LLMGraph no-code workflows (chat, RAG, automations) as MCP tools an assistant can invoke.

What you can do: Invoke a deployed LLMGraph workflow as a single MCP tool, passing an arbitrary input object through as the request body
Run chat-style workflows with a user message and optional conversation history
Register several deployments at once, each exposed as its own named tool with its own description and schema mode
Surface LLMGraph API errors (invalid key, blocked subscription, rate or budget limits, timeouts) back to the assistant as tool errors
When to use it: Useful when you have already built and deployed workflows on LLMGraph and want Claude Desktop, Claude Code, Cursor or another MCP client to call them directly, including chat assistants and RAG or automation pipelines.
Requirements: Runs locally over stdio, typically launched with npx, so Node.js 18 or newer is needed. Requires a deployed LLMGraph workflow: the deployment endpoint URL in LLMGRAPH_ENDPOINT and an API key in LLMGRAPH_API_KEY, both from the LLMGraph dashboard. Optional variables set the tool name, description, schema mode and timeout.

Before you install

The API key is a secret sent as the x-api-key header to the configured endpoint; client config files store it in plain text on your machine. Workflow runs may consume LLMGraph subscription budget and can be rate or budget limited. Tool calls send your inputs to the LLMGraph deployment, and the server can trigger workflows that perform automations.

Installation

In SourceWeft

Open Llmgraph in the dashboard and add it to a workspace.
Enable the server for the chats that should use its tools.

Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.

Other MCP clients

Follow the launch instructions in the repository.

README

@llmgraph/mcp-server

A Model Context Protocol (MCP) server that exposes your LLMGraph workflow deployments as MCP tools. Connect it to Claude Desktop, Claude Code, Cursor, or any other MCP client, and your assistant can invoke the workflows you built and deployed on LLMGraph.

Each configured deployment becomes one MCP tool. The server runs over stdio and is designed to be launched with npx, so there is nothing to install permanently.

Prerequisites

Node.js 18 or newer
A deployed LLMGraph workflow: copy the deployment endpoint URL (shaped like https://llmgraph.ai/api/<graph_id>/<environment>) and an API key from the LLMGraph dashboard

Configuration

All configuration is via environment variables.

Single deployment (simple path)

Variable	Required	Description
`LLMGRAPH_ENDPOINT`	yes	Full deployment endpoint URL copied from the dashboard
`LLMGRAPH_API_KEY`	yes	Secret API key for the deployment
`LLMGRAPH_TOOL_NAME`	no	Tool name shown to the client (default: `invoke_workflow`)
`LLMGRAPH_TOOL_DESCRIPTION`	no	Tool description shown to the model
`LLMGRAPH_SCHEMA_MODE`	no	`input` (default) or `chat`, see below
`LLMGRAPH_TIMEOUT_MS`	no	Request timeout in milliseconds, positive integer (default: `180000`). Applies in both single and multiple deployment modes.

Multiple deployments (advanced path)

Set LLMGRAPH_DEPLOYMENTS to a JSON array; each entry becomes one tool. When set, it takes precedence over the single-deployment variables.

json

[  {    "name": "summarize_document",    "description": "Summarizes a document with the LLMGraph summarizer workflow",    "endpoint": "https://llmgraph.ai/api/abc123/production",    "apiKey": "your-api-key"  },  {    "name": "support_bot",    "description": "Asks the support assistant workflow a question",    "endpoint": "https://llmgraph.ai/api/def456/production",    "apiKey": "your-other-api-key",    "inputSchema": "chat"  }]

[  {    "name": "summarize_document",    "description": "Summarizes a document with the LLMGraph summarizer workflow",    "endpoint": "https://llmgraph.ai/api/abc123/production",    "apiKey": "your-api-key"  },  {    "name": "support_bot",    "description": "Asks the support assistant workflow a question",    "endpoint": "https://llmgraph.ai/api/def456/production",    "apiKey": "your-other-api-key",    "inputSchema": "chat"  }]

Schema modes

input (default): the tool takes { "input": <object> } and the object is passed through unchanged as the POST body, so it works with any workflow input shape.
chat: for chat-style workflows. The tool takes { "user_input": <string>, "history": [{"role": "user"|"assistant", "content": <string>}] } (history optional) and sends it in the shape chat workflows expect.

Client setup

Claude Desktop

Add to claude_desktop_config.json (Settings, Developer, Edit Config):

json

{  "mcpServers": {    "llmgraph": {      "command": "npx",      "args": ["-y", "@llmgraph/mcp-server"],      "env": {        "LLMGRAPH_ENDPOINT": "https://llmgraph.ai/api/abc123/production",        "LLMGRAPH_API_KEY": "your-api-key",        "LLMGRAPH_TOOL_NAME": "summarize_document",        "LLMGRAPH_TOOL_DESCRIPTION": "Summarizes a document with my LLMGraph workflow"      }    }  }}

{  "mcpServers": {    "llmgraph": {      "command": "npx",      "args": ["-y", "@llmgraph/mcp-server"],      "env": {        "LLMGRAPH_ENDPOINT": "https://llmgraph.ai/api/abc123/production",        "LLMGRAPH_API_KEY": "your-api-key",        "LLMGRAPH_TOOL_NAME": "summarize_document",        "LLMGRAPH_TOOL_DESCRIPTION": "Summarizes a document with my LLMGraph workflow"      }    }  }}

Restart Claude Desktop and the tool appears in the tools menu.

Claude Code

bash

claude mcp add llmgraph \  --env LLMGRAPH_ENDPOINT=https://llmgraph.ai/api/abc123/production \  --env LLMGRAPH_API_KEY=your-api-key \  -- npx -y @llmgraph/mcp-server

claude mcp add llmgraph \  --env LLMGRAPH_ENDPOINT=https://llmgraph.ai/api/abc123/production \  --env LLMGRAPH_API_KEY=your-api-key \  -- npx -y @llmgraph/mcp-server

Cursor

Add to ~/.cursor/mcp.json (or .cursor/mcp.json in your project):

json

{  "mcpServers": {    "llmgraph": {      "command": "npx",      "args": ["-y", "@llmgraph/mcp-server"],      "env": {        "LLMGRAPH_ENDPOINT": "https://llmgraph.ai/api/abc123/production",        "LLMGRAPH_API_KEY": "your-api-key"      }    }  }}

{  "mcpServers": {    "llmgraph": {      "command": "npx",      "args": ["-y", "@llmgraph/mcp-server"],      "env": {        "LLMGRAPH_ENDPOINT": "https://llmgraph.ai/api/abc123/production",        "LLMGRAPH_API_KEY": "your-api-key"      }    }  }}

Error handling

Non-200 responses from the LLMGraph API are returned to the client as MCP tool errors carrying the API's error message:

Status	Meaning
400	invalid request body
401	missing or invalid API key
402	subscription blocked
403	API disabled or origin not allowed
404	unknown deployment or wrong API key
422	workflow run failed
429	rate or budget limited
504	workflow timed out

Security notes

LLMGraph API keys are secrets for server-side use. This server sends the key only as the x-api-key header of requests to your configured endpoint, and never writes it to stdout, stderr, or error messages.
Client config files like claude_desktop_config.json store the key in plain text on your machine; treat them accordingly.

Development

bash

npm installnpm run build   # compiles TypeScript to dist/npm test        # builds, then runs unit tests (node --test), no network calls

npm installnpm run build   # compiles TypeScript to dist/npm test        # builds, then runs unit tests (node --test), no network calls

License

MIT, see LICENSE.

Source: README.md at commit 35d0697

Tools

SourceWeft has not started this package in its sandbox yet, so its tools are not known.

Version history

v0.1.1LatestSep 16, 2026

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