Axom MCP Server
Provides persistent SQLite-based memory and unified tool abstraction for AI agents to support long-term context and complex tool chaining. It enables automated code analysis, file operations, and environment discovery through a standardized interface.
README
Axom MCP Server
Axom is a Model Context Protocol (MCP) server that provides persistent memory, tool abstraction, and chain-of-thought for AI agents.
Core Features
- Persistent Memory: Store and retrieve context across sessions using the Axom (SQLite) database.
- Tool Abstraction: Unified interface for memory, execution, analysis, discovery, and transformation.
- Chain Reactions: Execute tool sequences where outputs feed into the next step.
- AI-Powered Classification: Automatically categorizes memories by type and importance.
Quick Start
Axom runs as stdio MCP - your IDE spawns it automatically. No manual server startup needed.
Prerequisites
- Python 3.11+
- SQLite (included with Python)
- Git
Installation
Linux / macOS / WSL / Windows (Native)
Requires Git Bash, PowerShell, or a make provider.
git clone https://github.com/PugzUI/axom-mcp.git
cd axom-mcp
make install
What make install does:
- Installs Python dependencies.
- Installs Axom in editable mode (
pip install -e .). - Creates
.envfrom.env.example. - Configures all detected agents (Cursor, Trae, etc.).
- Installs Axom rules and skills for each agent.
Verification
make test # Run tests
Post-Install Check
Verify the local command is available:
command -v axom-mcp
Verify MCP initialization against the installed server:
python3 - <<'PY'
import asyncio
from mcp import ClientSession
from mcp.client.stdio import stdio_client, StdioServerParameters
async def main():
params = StdioServerParameters(command="axom-mcp", args=[])
async with stdio_client(params) as (read_stream, write_stream):
async with ClientSession(read_stream, write_stream) as session:
await session.initialize()
tools = await session.list_tools()
print("tool_count:", len(tools.tools))
asyncio.run(main())
PY
Client Configuration
make install automatically configures MCP for detected agents. The installer uses the best available command:
axom-mcp(if in PATH)axom(if in PATH)python -m axom_mcp.server(fallback)
See docs/agents/INDEX.md for detailed agent configuration.
For Zed, ~/.config/zed/settings.json should contain:
"context_servers": {
"axom": {
"command": "axom-mcp",
"args": []
}
}
Tools
Axom provides five core MCP tools:
axom_mcp_memory: Store and retrieve persistent context.axom_mcp_exec: File operations and shell commands with chaining.axom_mcp_analyze: Code analysis and debugging.axom_mcp_discover: Map environment and capabilities.axom_mcp_transform: Convert data between formats.
Documentation
- Architecture - System design and data flow.
- Tool Reference - Detailed tool parameters.
- Agent Guide - How to use Axom with AI agents.
- Troubleshooting - Common issues and fixes.
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
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 from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.