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Agent Knowledge

Community
itshare4u

Provides knowledge management capabilities through Elasticsearch integration, file system operations, and Git/SVN version control with 31 specialized tools for document indexing, sandboxed file operations, and automated version control workflows.

Publisheritshare4u
Repositoryagentknowledgemcp
LanguagePython
Forks
6
Stars
27
Available tools
27
Transport typestdio
Categories
LicenseMIT
Links
  • Connect tools to AI workflows

    Agent Knowledge exposes MCP capabilities that can be used by compatible AI clients and agents.

  • 27 available tools

    Browse the callable actions below, including names and descriptions when provided by the server.

  • Ready-to-copy setup

    Use the installation snippets to configure this server in your preferred MCP client.

  • Open source signals

    27 stars and 6 forks from the linked repository.

Agent Knowledge MCP 🔍

Complete knowledge management for AI assistants
MCP server with Elasticsearch search and document management.

Python 3.8+ MCP Compatible MIT License

🚀 Features

🔑 All-in-One Solution:

  • 🔍 Elasticsearch: Search, index, and manage documents
  • 📊 Document Validation: Schema-enforced structure
  • ⚙️ Configuration: Complete config management
  • 🛡️ Security: Sandboxed operations

✨ Benefits:

  • 🎯 20 Tools for knowledge management
  • 🤖 Works with any MCP-compatible AI (Claude, ChatGPT, VS Code, etc.)
  • 📚 Smart document management with validation
  • Elasticsearch integration for powerful search

⚡ Quick Start

Installation

bash
# Install with uvx (recommended)
uvx agent-knowledge-mcp

Setup for Claude Desktop

Add to claude_desktop_config.json:

json
{
  "mcpServers": {
    "agent-knowledge": {
      "command": "uvx",
      "args": ["agent-knowledge-mcp"]
    }
  }
}

Setup for VS Code

Install in VS Code

🛠️ What You Can Do

Try these with your AI assistant:

  • "Search documents for API authentication info"
  • "Index this document with proper tags"
  • "Create API documentation template"
  • "Find related documents on specific topics"
  • "Update configuration settings"
  • "Validate document structure"

🔧 Tools Overview

Tools for knowledge management:

CategoryToolsDescription
🔍 Elasticsearch9Search, index, manage documents
⚙️ Administration11Config, security, monitoring

🔒 Security & Configuration

Enterprise-grade security:

  • Sandboxed operations - Configurable access controls
  • Strict schema validation - Enforce document structure
  • Audit trails - Full operation logging
  • No cloud dependencies - Everything runs locally

Configuration example:

json
{
  "security": {
    "log_all_operations": true
  },
  "document_validation": {
    "strict_schema_validation": true,
    "allow_extra_fields": false
  }
}

🤝 Contributing & Support

Development

bash
git clone https://github.com/itshare4u/AgentKnowledgeMCP.git
cd AgentKnowledgeMCP
pip install -r requirements.txt
python3 src/main_server.py

Support the Project

Buy Me Coffee GitHub Sponsors


Transform your AI into a powerful knowledge management system! 🚀

MIT License - Complete knowledge management solution for AI assistants

Installation

TypingMind
Prerequisites:

Node.js 18+

{
  "mcpServers": {
    "agent-knowledge": {
      "command": "uvx",
      "args": [
        "agent-knowledge-mcp"
      ]
    }
  }
}

Available Tools

  • create_snapshot

    Create a snapshot (backup) of Elasticsearch indices with comprehensive options and repository management

  • restore_snapshot

    Restore indices from an Elasticsearch snapshot with comprehensive options and conflict resolution

  • list_snapshots

    List all snapshots in an Elasticsearch repository with detailed information and status

  • create_index_metadata

    Create metadata documentation for an Elasticsearch index to ensure proper governance and documentation

  • update_index_metadata

    Update existing metadata documentation for an Elasticsearch index

  • delete_index_metadata

    Delete metadata documentation for an Elasticsearch index

  • delete_document

    Delete a document from Elasticsearch index by document ID

  • get_document

    Retrieve a specific document from Elasticsearch index by document ID

  • index_document

    Index a document into Elasticsearch with smart duplicate prevention and intelligent document ID generation. 💡 RECOMMENDED: Use 'create_document_template' tool first to generate a proper document structure and avoid validation errors.

  • validate_document_schema

    Validate document structure against knowledge base schema and provide formatting guidance

  • create_document_template

    Create a properly structured document template for knowledge base with AI-generated metadata and formatting

  • create_index

    Create a new Elasticsearch index with optional mapping and settings configuration

  • delete_index

    Delete an Elasticsearch index and all its documents permanently

  • list_indices

    List all available Elasticsearch indices with document count and size statistics

  • search

    Search documents in Elasticsearch index with advanced filtering, pagination, and time-based sorting capabilities

  • batch_index_directory

    Batch index all documents from a directory into Elasticsearch with AI-enhanced metadata generation and comprehensive file processing

  • get_config

    Get the complete configuration from config.json file with formatted display

  • update_config

    Update configuration with section-specific changes or full configuration replacement

  • validate_config

    Validate configuration object structure, types, and values with comprehensive error reporting

  • reload_config

    Reload configuration from config.json file and reinitialize all components with updated settings

  • setup_elasticsearch

    Auto-setup Elasticsearch using Docker with optional Kibana and force recreate options

  • elasticsearch_status

    Check status of Elasticsearch and Kibana containers with detailed configuration information

  • server_status

    Check current server status, version, and available updates with comprehensive system information

  • server_upgrade

    Upgrade this MCP server when installed via uvx with automatic configuration backup and restoration

  • ask_user_advice

    Ask user for advice when agent encounters uncertainty, problems, or needs guidance. Use this when you're unsure about something or need human input to proceed properly.

  • reset_config

    Reset config.json to defaults from config.default.json (manual reset - overwrites current config)

  • ask_mcp_advice

    Advanced project guidance using AI-filtered knowledge from .knowledges directory

Use Agent Knowledge MCP with multiple AI models

TypingMind connects MCP tools at the workspace level, so once Agent Knowledge is connected, you can use it with different AI models in TypingMind instead of setting it up separately for each model. This MCP runs locally through the TypingMind MCP connector on your device.

Setup guide to use the local connector

Use this when the MCP server needs access to local files, apps, or private resources on your computer.

1

Open the MCP settings

In TypingMind, go to Settings, Advanced Settings, then Model Context Protocol and choose Setup Connector.

  1. Open TypingMind in your browser.
  2. Click the Settings icon.
  3. Go to Advanced Settings.
  4. Open the Model Context Protocol section.
  5. Click Setup Connector and choose This Device.
TypingMind MCP connector setup screen with This Device selected
2

Run the connector command

Choose This Device, copy the command from TypingMind, and run it in Terminal. Keep the process running while you use MCP.

  1. Copy the setup command shown by TypingMind.
  2. Open Terminal on macOS or Windows Terminal on Windows.
  3. Paste and run the command.
  4. Approve the package install if Terminal asks you to proceed.
  5. Keep the Terminal window running while using MCP tools.
3

Add Agent Knowledge as a server

When the connector status is Ready, click Edit Servers and paste the MCP server configuration.

  1. Wait until the connector status shows Ready.
  2. Click Edit Servers.
  3. Paste the Agent Knowledge MCP server configuration.
  4. Save the server list.
  5. Refresh if you want to confirm the connector is still ready.
TypingMind MCP settings showing active server and Edit Servers button
{
  "mcpServers": {
    "agent-knowledge": {
      "command": "npx",
      "args": [
        "-y",
        "agent-knowledge-mcp"
      ]
    }
  }
}
4

Use it across models

Save the server list, open Plugins, enable the Agent Knowledge MCP tools, then select any supported AI model in TypingMind and use the tools in chat or assign them to an AI agent.

  1. Open the Plugins page in TypingMind.
  2. Enable the Agent Knowledge MCP tools.
  3. Start a chat and choose the AI model you want to use.
  4. Use the MCP tools in chat or assign them to an AI agent.
  5. Switch to another AI model whenever needed without reconnecting MCP.
TypingMind chat using enabled MCP tools with a selected AI model
Can you use Agent Knowledge to help me with this task?
Agent Knowledge
Sure. I read it.
Here is what I found using Agent Knowledge.

Frequently asked questions

What is the Agent Knowledge MCP server used for?

Agent Knowledge is an MCP server that lets compatible AI clients connect to external tools and context. In TypingMind, you can add this MCP server once and make its tools available in your AI workspace.

Can I use Agent Knowledge MCP with multiple AI models in TypingMind?

Yes. TypingMind connects MCP tools at the workspace level, so you can use Agent Knowledge with different AI models such as Claude, ChatGPT, Gemini, or other models you have configured in TypingMind without setting up the MCP server separately for each model.

Why use Agent Knowledge MCP with TypingMind?

TypingMind is one of the best frontends for LLM chat because it brings multiple AI models, prompts, plugins, AI agents, API keys, and MCP tools into one workspace. With Agent Knowledge connected, you can use its MCP tools across your preferred models while keeping your chat workflow organized in TypingMind.

How do I connect Agent Knowledge MCP to TypingMind?

Agent Knowledge runs through the TypingMind local MCP connector. This is best when the MCP server needs access to local files, desktop apps, command-line tools, or private resources on your computer.

What tools does Agent Knowledge MCP provide in TypingMind?

Agent Knowledge exposes 27 MCP tools that can be enabled from the TypingMind Plugins page and used in chat or assigned to AI agents.

Do I need to share my API keys with TypingMind to use Agent Knowledge MCP?

No. TypingMind is local-first and lets you keep your model providers, API keys, prompts, and MCP configuration under your control. If Agent Knowledge requires authentication, add the required headers, OAuth settings, or local configuration for that MCP server when you create the connection.

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