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MCP Server: Maximize ML Performance & Future-Proof AI - MCP Implementation

MCP Server: Maximize ML Performance & Future-Proof AI

Maximize ML model performance on Graphlit with the Model Context Protocol (MCP) Server – seamlessly deploy, scale, and optimize AI workflows. Future-proof your platform, today.

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About MCP Server

What is MCP Server: Maximize ML Performance & Future-Proof AI?

The MCP Server is a middleware solution designed to streamline data integration, preprocessing, and analysis for machine learning workflows. It acts as a universal bridge between diverse data sources and AI models, ensuring seamless compatibility with evolving AI frameworks. By automating data normalization and providing standardized APIs, it future-proofs enterprise AI initiatives against rapid technological changes.

How to use MCP Server: Maximize ML Performance & Future-Proof AI?

Implementation involves three core steps: 1) Configure environment variables with organization credentials, 2) Deploy via npm package managers in supported clients like Cursor or Smithery, 3) Authorize data connectors through dedicated API tokens. The server exposes RESTful endpoints for real-time data queries and batch processing, with multi-stage authentication for secure access control.

MCP Server Features

Key Features of MCP Server: Maximize ML Performance & Future-Proof AI?

  • Cross-platform data ingestion from 20+ enterprise systems including Slack, GitHub, and Jira
  • AutoML-ready data normalization with on-the-fly schema mapping
  • Websocket-based real-time data streaming for low-latency pipelines
  • Granular access controls with role-based permissions
  • Performance dashboards for latency tracking and resource utilization

Use cases of MCP Server: Maximize ML Performance & Future-Proof AI?

Deployed scenarios include: 1) Preprocessing customer support logs from Zendesk for NLP model training, 2) Unifying sales data from multiple CRMs for predictive analytics, 3) Creating audit trails for regulatory compliance in financial systems. The server's modular architecture allows adding new data connectors via plugin system for emerging data formats.

MCP Server FAQ

FAQ from MCP Server: Maximize ML Performance & Future-Proof AI?

Does MCP Server handle GDPR compliance?

Yes, includes field-level encryption and automated data anonymization modules.

What scaling options are available?

Supports Kubernetes deployments with auto-scaling based on API request volumes.

How is version compatibility maintained?

Implements semantic versioning with backward compatibility guarantees for major releases.

Content

npm version smithery badge

Model Context Protocol (MCP) Server for Graphlit Platform

Overview

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. This document outlines the setup process and provides a basic example of using the client.

Ingest anything from Slack, Discord, websites, Google Drive, email, Jira, Linear or GitHub into a Graphlit project - and then search and retrieve relevant knowledge within an MCP client like Cursor, Windsurf or Cline.

Documents (PDF, DOCX, PPTX, etc.) and HTML web pages will be extracted to Markdown upon ingestion.

Audio and video files will be transcribed upon ingestion.

Web crawling and web search are available as MCP tools, with no need to integrate Firecrawl, Exa, etc. separately.

You can read more about the MCP Server use cases and features on our blog.

graphlit-mcp-server MCP server

Tools

Retrieval

  • Query Contents
  • Query Collections
  • Retrieve Relevant Sources
  • Retrieve Similar Images
  • Visually Describe Image

Extraction

  • Extract Structured JSON from Text

Ingestion

  • Files
  • Web Pages
  • Text

Data Connectors

  • Microsoft Outlook email
  • Google Mail
  • Notion
  • Reddit
  • Linear
  • Jira
  • GitHub Issues
  • Google Drive
  • OneDrive
  • SharePoint
  • Dropbox
  • Box
  • GitHub
  • Slack
  • Microsoft Teams
  • Discord
  • Podcasts (RSS)

Web

  • Web Crawling
  • Web Search (including Podcast Search)
  • Web Mapping
  • Screenshot Page

Notifications

  • Slack
  • Email
  • Webhook

Operations

  • Configure Project
  • Create Collection
  • Add Contents to Collection
  • Remove Contents from Collection
  • Delete Collection
  • Delete Feed(s)
  • Delete Content(s)
  • Is Feed Done?
  • Is Content Done?

Enumerations

  • List Slack Channels
  • List Microsoft Teams Teams
  • List Microsoft Teams Channels
  • List SharePoint Libraries
  • List SharePoint Folders
  • List Linear Projects

Resources

  • Project
  • Contents
  • Feeds
  • Collections (of Content)
  • Workflows
  • Specifications

Prerequisites

Before you begin, ensure you have the following:

  • Node.js installed on your system (recommended version 18.x or higher).
  • An active account on the Graphlit Platform with access to the API settings dashboard.

Configuration

The Graphlit MCP Server supports environment variables to be set for authentication and configuration:

  • GRAPHLIT_ENVIRONMENT_ID: Your environment ID.
  • GRAPHLIT_ORGANIZATION_ID: Your organization ID.
  • GRAPHLIT_JWT_SECRET: Your JWT secret for signing the JWT token.

You can find these values in the API settings dashboard on the Graphlit Platform.

Installation

Installing via Windsurf

To install graphlit-mcp-server in Windsurf IDE application, Cline should use NPX:

npx -y graphlit-mcp-server

Your mcp_config.json file should be configured similar to:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "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",
            }
        }
    }
}

Installing via Cline

To install graphlit-mcp-server in Cline IDE application, Cline should use NPX:

npx -y graphlit-mcp-server

Your cline_mcp_settings.json file should be configured similar to:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "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",
            }
        }
    }
}

Installing via Cursor

To install graphlit-mcp-server in Cursor IDE application, Cline should use NPX:

npx -y graphlit-mcp-server

Your mcp.json file should be configured similar to:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "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",
            }
        }
    }
}

Installing via Smithery

To install graphlit-mcp-server for Claude Desktop automatically via Smithery:

npx -y @smithery/cli install @graphlit/graphlit-mcp-server --client claude

Installing manually

To use the Graphlit MCP Server in any MCP client application, use:

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "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",
            }
        }
    }
}

Optionally, you can configure the credentials for data connectors, such as Slack, Google Email and Notion. Only GRAPHLIT_ORGANIZATION_ID, GRAPHLIT_ENVIRONMENT_ID and GRAPHLIT_JWT_SECRET are required.

{
    "mcpServers": {
        "graphlit-mcp-server": {
            "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": "your-slack-bot-token",
                "DISCORD_BOT_TOKEN": "your-discord-bot-token",
                "GOOGLE_EMAIL_REFRESH_TOKEN": "your-google-refresh-token",
                "GOOGLE_EMAIL_CLIENT_ID": "your-google-client-id",
                "GOOGLE_EMAIL_CLIENT_SECRET": "your-google-client-secret",
                "LINEAR_API_KEY": "your-linear-api-key",
                "GITHUB_PERSONAL_ACCESS_TOKEN": "your-github-pat",
                "JIRA_EMAIL": "your-jira-email",
                "JIRA_TOKEN": "your-jira-token",
                "NOTION_API_KEY": "your-notion-api-key",
                "NOTION_DATABASE_ID": "your-notion-database-id"
            }
        }
    }
}

Support

Please refer to the Graphlit API Documentation.

For support with the Graphlit MCP Server, please submit a GitHub Issue.

For further support with the Graphlit Platform, please join our Discord community.

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