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Graphlit MCP

v1.0.20260112001•Search & Data Extraction•stable

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents

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What is Graphlit MCP?

Graphlit MCP is a Model Context Protocol (MCP) server that allows AI assistants like Claude, Cursor, and VS Code to model context protocol (mcp) server enables integration between mcp clients and the graphlit service. ingest anything from slack to gmail to podcast feeds, in addition to web crawling, into a graphlit...

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents

This server falls under the Search & Data Extraction category on MCPgee, the world's largest MCP server directory with 33,000+ servers.

Features

  • The Model Context Protocol (MCP) Server enables integration

Use Cases

Multi-source content ingestion
Slack, Gmail, podcast integration
RAG content retrieval
graphlit

Maintainer

LicenseMIT License
Languagetypescript
Versionv1.0.20260112001
UpdatedMay 21, 2026
Statushealthy
Maintenanceactive

Works with

ClaudeOpenAIwindowsmacoslinux
View SourceBrowse All Servers

Installation

NPM

npx -y graphlit-mcp-server

Manual Installation

npx -y graphlit-mcp-server

Configuration

Configuration Details

Config File

claude_desktop_config.json

Performance

Response Metrics

Response Time< 200ms
ThroughputMedium

Resource Usage

Memory UsageLow
CPU UsageLow

How to Set Up and Use Graphlit MCP

The Graphlit MCP Server connects AI assistants to the Graphlit knowledge management platform, enabling ingestion of content from 20+ sources — including Slack, Gmail, GitHub, Notion, Jira, Discord, web pages, and podcast feeds — and then retrieval of relevant content via semantic search and RAG. Once content is ingested into a Graphlit project, the MCP server lets you query, summarize, and reason over that unified knowledge base directly in your AI conversations.

Prerequisites

  • Node.js 18.x or higher
  • A Graphlit Platform account with an active project (sign up at app.graphlit.io)
  • Graphlit API credentials: Organization ID, Environment ID, and JWT Secret from the platform's API settings
  • An MCP-compatible client such as Claude Desktop, Claude Code, or VS Code
  • Optional: API tokens for data sources you want to ingest (Slack bot token, GitHub PAT, Notion API key, etc.)
1

Create a Graphlit account and project

Sign up at app.graphlit.io and create a new project. Navigate to API Settings to retrieve your Organization ID, Environment ID, and JWT Secret.

2

Note your three required credentials

You need exactly three values from the Graphlit dashboard: GRAPHLIT_ORGANIZATION_ID, GRAPHLIT_ENVIRONMENT_ID, and GRAPHLIT_JWT_SECRET. These authenticate all MCP tool calls.

3

Optionally gather connector credentials

If you want to ingest from specific sources, gather the relevant tokens now. For example, a Slack bot token for Slack ingestion, a GitHub personal access token for repository content, or a Notion API key.

# Example connector tokens (set only what you need)
export SLACK_BOT_TOKEN="xoxb-..."
export GITHUB_PERSONAL_ACCESS_TOKEN="ghp_..."
export NOTION_API_KEY="secret_..."
export LINEAR_API_KEY="lin_api_..."
4

Add the Graphlit MCP server to your client configuration

Add the graphlit-mcp-server entry to your claude_desktop_config.json with all required environment variables.

5

Restart your MCP client and ingest content

Restart Claude Desktop. Then use the MCP tools to ingest your first content — for example, ask Claude to crawl a web page or ingest a Slack channel into your Graphlit project.

6

Query your knowledge base

After ingestion, use the retrieval tools to search and reason over your content. Ask questions that span multiple ingested sources.

Graphlit MCP Examples

Client configuration

claude_desktop_config.json entry for Graphlit MCP Server with required credentials and optional Slack connector.

{
  "mcpServers": {
    "graphlit": {
      "command": "npx",
      "args": ["-y", "graphlit-mcp-server"],
      "env": {
        "GRAPHLIT_ORGANIZATION_ID": "your-organization-id",
        "GRAPHLIT_ENVIRONMENT_ID": "your-environment-id",
        "GRAPHLIT_JWT_SECRET": "your-jwt-secret",
        "SLACK_BOT_TOKEN": "xoxb-your-slack-bot-token",
        "GITHUB_PERSONAL_ACCESS_TOKEN": "ghp_your-github-token"
      }
    }
  }
}

Prompts to try

Sample prompts for ingesting content and querying your Graphlit knowledge base.

- "Crawl https://docs.example.com and ingest all pages into my Graphlit project"
- "Ingest the last 30 days of messages from the #engineering Slack channel"
- "Search my Graphlit knowledge base for discussions about the API rate limiting issue"
- "Summarize the key decisions made in my ingested meeting transcripts this week"
- "Query my Graphlit project for all content related to the authentication redesign"
- "Ingest my Gmail inbox for emails from the last week and find action items"

Troubleshooting Graphlit MCP

Authentication error: invalid JWT or organization not found

Double-check all three required credentials from the Graphlit dashboard: GRAPHLIT_ORGANIZATION_ID, GRAPHLIT_ENVIRONMENT_ID, and GRAPHLIT_JWT_SECRET. These are distinct values — do not swap the environment ID and organization ID.

Connector ingestion fails for Slack or GitHub

Verify the connector-specific token is correctly set (e.g. SLACK_BOT_TOKEN must start with xoxb-). For Slack, ensure the bot is installed in your workspace and has permission to read the target channels. For GitHub, confirm the PAT has repo read scope.

npx fails on Windows with a path or execution error

On Windows, prefix the command with the full cmd.exe path: set command to 'C:\\Windows\\System32\\cmd.exe' and args to ['/c', 'npx', '-y', 'graphlit-mcp-server']. This is a known Windows npx execution issue.

Frequently Asked Questions about Graphlit MCP

What is Graphlit MCP?

Graphlit MCP is a Model Context Protocol (MCP) server that model context protocol (mcp) server enables integration between mcp clients and the graphlit service. ingest anything from slack to gmail to podcast feeds, in addition to web crawling, into a graphlit project - and then retrieve relevant contents It connects AI assistants to external tools and data sources through a standardized interface.

How do I install Graphlit MCP?

Install via npm with the command: npx -y graphlit-mcp-server. Then add the server configuration to your AI client's JSON config file (e.g., claude_desktop_config.json or .cursor/mcp.json).

Which AI clients work with Graphlit MCP?

Graphlit MCP works with all major MCP-compatible AI clients including Claude Desktop, Claude Code, Cursor, VS Code (GitHub Copilot), Windsurf, and Cline.

Is Graphlit MCP free to use?

Yes, Graphlit MCP is open source and available under the MIT License license. You can use it freely in both personal and commercial projects.

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Quick Config Preview

{ "mcpServers": { "graphlit-mcp-server": { "command": "npx", "args": ["-y", "graphlit-mcp-server"] } } }

Add this to your claude_desktop_config.json or .cursor/mcp.json

Read the full setup guide →

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