ai.zine/mcp

AI 与智能体

by graphlit

让你的记忆随 AI 到处可用。知识只需构建一次,即可通过 MCP 在任何支持处随时访问。

把分散知识沉淀成可被 AI 随处调用的长期记忆,基于 MCP 一次构建多端复用,特别适合常换工具的开发者。

什么是 ai.zine/mcp

让你的记忆随 AI 到处可用。知识只需构建一次,即可通过 MCP 在任何支持处随时访问。

README

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, Goose or Cline.

Your Graphlit project acts as a searchable, and RAG-ready knowledge base across all your developer and product management tools.

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 built-in as MCP tools, with no need to integrate other tools like Firecrawl, Exa, etc. separately.

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

Watch our latest YouTube video on using the Graphlit MCP Server with the Goose MCP client.

For any questions on using the MCP Server, please join our Discord community and post on the #mcp channel.

<a href="https://glama.ai/mcp/servers/fscrivteod"> <img width="380" height="200" src="https://glama.ai/mcp/servers/fscrivteod/badge" alt="graphlit-mcp-server MCP server" /> </a>

Tools

Retrieval

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

RAG

  • Prompt LLM Conversation

Extraction

  • Extract Structured JSON from Text

Publishing

  • Publish as Audio (ElevenLabs Audio)
  • Publish as Image (OpenAI Image Generation)

Ingestion

  • Files
  • Web Pages
  • Messages
  • Posts
  • Emails
  • Issues
  • Text
  • Memory (Short-Term)

Data Connectors

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

Web

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

Notifications

  • Slack
  • Email
  • Webhook
  • Twitter/X

Operations

  • Configure Project
  • Create Collection
  • Add Contents to Collection
  • Remove Contents from Collection
  • Delete Collection(s)
  • Delete Feed(s)
  • Delete Content(s)
  • Delete Conversation(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
  • List Notion Databases
  • List Notion Pages
  • List Dropbox Folders
  • List Box Folders
  • List Discord Guilds
  • List Discord Channels
  • List Google Calendars
  • List Microsoft Calendars

Resources

  • Project
  • Contents
  • Feeds
  • Collections (of Content)
  • Workflows
  • Conversations
  • 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 VS Code

For quick installation, use one of the one-click install buttons below:

Install with NPX in VS Code Install with NPX in VS Code Insiders

For manual installation, add the following JSON block to your User Settings (JSON) file in VS Code. You can do this by pressing Ctrl + Shift + P and typing Preferences: Open User Settings (JSON).

Optionally, you can add it to a file called .vscode/mcp.json in your workspace. This will allow you to share the configuration with others.

Note that the mcp key is not needed in the .vscode/mcp.json file.

json
{
  "mcp": {
    "inputs": [
      {
        "type": "promptString",
        "id": "organization_id",
        "description": "Graphlit Organization ID",
        "password": true
      },
      {
        "type": "promptString",
        "id": "environment_id",
        "description": "Graphlit Environment ID",
        "password": true
      },
      {
        "type": "promptString",
        "id": "jwt_secret",
        "description": "Graphlit JWT Secret",
        "password": true
      }
    ],
    "servers": {
      "graphlit": {
        "command": "npx",
        "args": ["-y", "graphlit-mcp-server"],
        "env": {
          "GRAPHLIT_ORGANIZATION_ID": "${input:organization_id}",
          "GRAPHLIT_ENVIRONMENT_ID": "${input:environment_id}",
          "GRAPHLIT_JWT_SECRET": "${input:jwt_secret}"
        }
      }
    }
  }
}

Installing via Windsurf

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

bash
npx -y graphlit-mcp-server

Your mcp_config.json file should be configured similar to:

code
{
    "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:

bash
npx -y graphlit-mcp-server

Your cline_mcp_settings.json file should be configured similar to:

code
{
    "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, Cursor should use NPX:

bash
npx -y graphlit-mcp-server

Your mcp.json file should be configured similar to:

code
{
    "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:

bash
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:

code
{
    "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.

code
{
    "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",
                "TWITTER_TOKEN": "your-twitter-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"
            }
        }
    }
}

NOTE: when running 'npx' on Windows, you may need to explicitly call npx via the command prompt.

code
"command": "C:\\Windows\\System32\\cmd.exe /c npx"

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.

常见问题

ai.zine/mcp 是什么?

让你的记忆随 AI 到处可用。知识只需构建一次,即可通过 MCP 在任何支持处随时访问。

相关 Skills

Claude接口

by anthropics

Universal
热门

面向接入 Claude API、Anthropic SDK 或 Agent SDK 的开发场景,自动识别项目语言并给出对应示例与默认配置,快速搭建 LLM 应用。

想把Claude能力接进应用或智能体,用claude-api上手快、兼容Anthropic与Agent SDK,集成路径清晰又省心

AI 与智能体
未扫描109.6k

提示工程专家

by alirezarezvani

Universal
热门

覆盖Prompt优化、Few-shot设计、结构化输出、RAG评测与Agent工作流编排,适合分析token成本、评估LLM输出质量,并搭建可落地的AI智能体系统。

把提示优化、LLM评测到RAG与智能体设计串成一套方法,适合想系统提升AI开发效率的人。

AI 与智能体
未扫描9.0k

智能体流程设计

by alirezarezvani

Universal
热门

面向生产级多 Agent 编排,梳理顺序、并行、分层、事件驱动、共识五种工作流设计,覆盖 handoff、状态管理、容错重试、上下文预算与成本优化,适合搭建复杂 AI 协作系统。

帮你把多智能体流程设计、编排和自动化统一起来,复杂工作流也能更稳地落地,适合追求强控制力的团队。

AI 与智能体
未扫描9.0k

相关 MCP Server

顺序思维

编辑精选

by Anthropic

热门

Sequential Thinking 是让 AI 通过动态思维链解决复杂问题的参考服务器。

这个服务器展示了如何让 Claude 像人类一样逐步推理,适合开发者学习 MCP 的思维链实现。但注意它只是个参考示例,别指望直接用在生产环境里。

AI 与智能体
82.9k

知识图谱记忆

编辑精选

by Anthropic

热门

Memory 是一个基于本地知识图谱的持久化记忆系统,让 AI 记住长期上下文。

帮 AI 和智能体补上“记不住”的短板,用本地知识图谱沉淀长期上下文,连续对话更聪明,数据也更可控。

AI 与智能体
82.9k

PraisonAI

编辑精选

by mervinpraison

热门

PraisonAI 是一个支持自反思和多 LLM 的低代码 AI 智能体框架。

如果你需要快速搭建一个能 24/7 运行的 AI 智能体团队来处理复杂任务(比如自动研究或代码生成),PraisonAI 的低代码设计和多平台集成(如 Telegram)让它上手极快。但作为非官方项目,它的生态成熟度可能不如 LangChain 等主流框架,适合愿意尝鲜的开发者。

AI 与智能体
6.4k

评论