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MCP Server Setup

⏱️ Time to Complete: 10 minutes 🎯 Level: Beginner 💻 Language: TypeScript (MCP Server)

What You'll Build

  • ✅ Connect Graphlit to your MCP-compatible IDE (Cursor, Windsurf, Claude Desktop, Cline)

  • ✅ Search your Graphlit project (Slack, Gmail, Notion, etc.) from your editor

  • ✅ Query conversations, collections, feeds, and workflows

  • ✅ Ingest new content or trigger workflows without leaving the IDE

📁 Graphlit MCP Server Repository

Prerequisites

  • Node.js 18+

  • One of the MCP-aware IDEs (Cursor, Windsurf, Claude Desktop, or VS Code with Cline)

  • Graphlit credentials in .env (from Getting Started guide):

    • GRAPHLIT_ORGANIZATION_ID

    • GRAPHLIT_ENVIRONMENT_ID

    • GRAPHLIT_JWT_SECRET

  • npm install -g graphlit-mcp-server (or use npx in configs below)

Need Graphlit code examples? Check out Ask Graphlit - an AI assistant that generates Graphlit SDK code in Python, TypeScript, or .NET. This MCP integration is for accessing your data (Slack, Gmail, content), not for code help.

Setup

The Graphlit MCP Server exposes your actual Graphlit project: contents, feeds, collections, workflows, conversations, and specifications.

Environment

Create .env with your Graphlit credentials (from Getting Started):

GRAPHLIT_ORGANIZATION_ID=your_org_id_from_portal
GRAPHLIT_ENVIRONMENT_ID=your_env_id_from_portal
GRAPHLIT_JWT_SECRET=your_jwt_secret_from_portal

Install and test locally:

npm install -g graphlit-mcp-server
# or npx graphlit-mcp-server
npx graphlit-mcp-server --test

IDE Configuration

Cursor / Windsurf / Cline / Claude Desktop

{
  "mcpServers": {
    "graphlit": {
      "command": "npx",
      "args": ["graphlit-mcp-server"],
      "env": {
        "GRAPHLIT_ORGANIZATION_ID": "${GRAPHLIT_ORGANIZATION_ID}",
        "GRAPHLIT_ENVIRONMENT_ID": "${GRAPHLIT_ENVIRONMENT_ID}",
        "GRAPHLIT_JWT_SECRET": "${GRAPHLIT_JWT_SECRET}"
      }
    }
  }
}

Restart your IDE. Graphlit will appear alongside other MCP tools.

Key MCP Tools (from graphlit-mcp-server)

The server registers 60+ tools via registerTools:

Category
Examples

Retrieval

queryContents, queryCollections, queryFeeds, queryConversations, retrieveRelevantSources

Conversations

promptConversation (streams via MCP channel)

Ingestion

ingestFile, ingestText, ingestWebPage, ingestEmail, ingestIssue, ingestMessage, ingestFeed

Publishing

publishAudio, publishImage

Operations

configureProject, createCollection, addContentsToCollection, deleteContent, isContentDone

Enumerations

listSlackChannels, listNotionDatabases, listLinearProjects, listGoogleCalendars, etc.

All enumerations, types, and arguments match the TypeScript SDK. For example:

import {
  FeedTypes,
  FeedListingTypes,
  EmailListingTypes,
  SearchServiceTypes,
} from 'graphlit-client/dist/generated/graphql-types';

Use these same enums in MCP prompts when specifying properties.

Example Prompts (Local Server)

Search Company Knowledge

@graphlit query_contents search="redis failover" searchType=HYBRID limit=5

Scope by Collection + Entity

@graphlit query_contents search="pricing" searchType=HYBRID collections=["${GRAPHLIT_COLLECTION_SUPPORT}"] observations=[{"type":"ORGANIZATION","observable":{"id":"${GRAPHLIT_ORG_ACME}"}}]

Ingest a File

@graphlit ingest_file path="./runbooks/cache-playbook.pdf" workflow={"id":"${WORKFLOW_ID}"} isSynchronous=true

Prompt a Conversation

@graphlit prompt_conversation id="${CONVERSATION_ID}" prompt="Summarize the last three incidents for Acme Corp and list remaining blockers."

The MCP server streams token updates back to the IDE when using promptConversation.

Integrating with Other MCP Servers

Combine Graphlit with filesystem, GitHub, database or cloud MCP servers in one config:

{
  "mcpServers": {
    "graphlit": { ... },
    "filesystem": {
      "command": "npx",
      "args": ["@modelcontextprotocol/server-filesystem", "/path/to/code"]
    },
    "github": {
      "command": "npx",
      "args": ["@modelcontextprotocol/server-github"],
      "env": { "GITHUB_TOKEN": "${GITHUB_TOKEN}" }
    }
  }
}

Now your AI can pull:

  • Local source files

  • Open PRs and discussions

  • Production incidents stored in Graphlit

  • Slack, email, meetings tied to an account

Production Tips

  1. Separate projects per tenant/team: set GRAPHLIT_ENVIRONMENT_ID per MCP entry.

  2. Persist identifiers: store collection/workflow IDs in env vars to reuse across prompts.

  3. Use isContentDone before prompting to avoid stale context on newly ingested data.

  4. Secure secrets: reference OS-level environment variables (${VAR}) instead of hardcoding values.

  5. Log tool output: Cursor and Claude show MCP logs; use them to audit retrieved sources.

Troubleshooting

  • Run npx graphlit-mcp-server --test to validate credentials.

  • Confirm Node.js 18+ and that graphlit-client installs without errors.

  • OAuth-based tools (Slack, Gmail, GitHub) require tokens in the environment; follow instructions in the MCP server README.

  • If tools fail, inspect IDE MCP logs; most errors surface there (stdout/stderr).

Next Steps

With MCP + Graphlit, your IDE has direct access to the same semantic memory your production agents use. Build smarter tooling without leaving the editor.

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