agent-context-mcp
Allows reading Hermes conversation history, including listing, searching, and retrieving conversations in a sanitized format.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@agent-context-mcpshow me the latest Codex conversation about the login bug"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
agent-context-mcp
One privacy-first MCP server for developers who work across AI coding agents.
Move between Claude Code, Codex, and Hermes without re-explaining what happened. agent-context-mcp reads the useful parts of your local agent history, sanitizes them, and returns structured Markdown through one MCP interface.
Local-first. Read-only. Sanitized before output.
Why this exists
When you switch AI coding tools, each one starts without the decisions, failures, and next steps from the others. This server gives a selected client a safe, read-only view of local context from:
Claude Code
Codex
Hermes
It also discovers local AI harnesses, MCP configurations, and CLI runtimes — and can generate dry-run proposals for skills or MCP migration.
Related MCP server: Colab MCP
Your sessions stay local
agent-context-mcp is not a session-sync product.
No hosted service by default
No telemetry or analytics
No background uploads
No writes to source session stores
No secrets, raw configuration values, or auth headers returned
No remote network connection unless you explicitly enable and deploy one
Before output, source adapters exclude system/developer instructions, bootstrap dumps, encrypted/internal reasoning, and secret-shaped values. Tool output is opt-in and bounded. Active JSONL files with a partial trailing line are tolerated.
Never commit your agent data. This repository ignores session stores, JSONL files, local databases, credentials, and .env files. Its tests check for personal Windows paths and project-specific markers.
Install
From source (current)
git clone https://github.com/mosafly/agent-context-mcp.git
cd agent-context-mcp
python -m pip install .Requires Python 3.10+.
Claude Code
claude mcp add --scope user agent_context -- agent-context-mcpCodex CLI
codex mcp add agent_context -- agent-context-mcpHermes
hermes mcp add agent_context --command agent-context-mcpClaude Desktop
Add this to claude_desktop_config.json and restart Claude Desktop:
{
"mcpServers": {
"agent_context": {
"command": "agent-context-mcp",
"args": []
}
}
}Start a new client session after installing so the MCP tool cache refreshes.
One unified interface
All conversation tools take a source:
hermes | codex | claude_codeTool | Purpose |
| List sanitized local conversations |
| Search sanitized text |
| Read one selected conversation |
| Read the latest conversation |
| Produce a bounded handoff bundle without writing a file |
| Detect known local AI harnesses |
| Discover MCP names without secret values |
| Locate CLI runtimes without launching desktop apps |
| Produce a skill migration dry-run |
| Produce a sanitized MCP migration dry-run |
Migration proposals never edit configuration, copy skills, install packages, or transfer credentials.
Supported clients
Client | Local | Remote HTTPS |
Claude Code | ✅ | — |
Codex CLI | ✅ | — |
Hermes / Hermes CLI | ✅ | — |
Claude Desktop | ✅ | — |
Claude Cowork / claude.ai | ❌ | ✅ via an authenticated gateway |
ChatGPT Desktop / Web | ❌ | ✅ via an authenticated gateway |
Cloud clients cannot access your localhost or execute a local stdio command. Do not expose this server directly to the public internet.
Optional local HTTP mode
The default transport is stdio. A local Streamable HTTP server is available only after an explicit opt-in:
AGENT_CONTEXT_ALLOW_HTTP=1 agent-context-mcp \
--transport streamable-http \
--host 127.0.0.1 \
--port 8000For Cowork, claude.ai, ChatGPT, or any cloud client, place an authenticated HTTPS gateway in front of the service. Require OAuth or equivalent authentication, rate limits, and a deliberate deployment decision. Never publish a direct session reader without those controls.
Configuration
The bundled adapters use local defaults for common session locations. Set these environment variables only when your stores live elsewhere:
CODEX_SESSIONS_ROOT
CLAUDE_PROJECTS_ROOT
HERMES_HOMEPaths are read locally; their contents are never uploaded by this package.
Development
python -m pip install -e .
python -m unittest discover -s tests
python -m py_compile src/agent_context_mcp/*.py src/agent_context_mcp/adapters/*.pyLicense
MIT. See LICENSE.
This server cannot be deployed
Maintenance
Related MCP Connectors
Your coding agent tells a coworker's agent what you found or changed. Invite-only.
Shared memory for coding agents. Stop re-explaining your codebase every session.
One searchable history across every AI coding tool, with secret scanning and a shared task board.
- OneLoreOAuthai.onelore
Shared project context for AI agents and teams: docs, tasks, and messages that stay current.
Related MCP Servers
- AlicenseAqualityDmaintenanceAllows AI assistants to access and analyze your Cursor conversation history, enabling personalized coding assistance based on your actual development patterns.88 npm33MIT
- AlicenseNot gradedqualityNot gradedmaintenanceEnables AI coding assistants like Claude Code, Cursor, and Codex to share chat logs, terminal history, and session context with each other. Eliminates the need to re-explain context when switching between different AI coding tools.2MIT
- AlicenseNot gradedqualityDmaintenanceEnables handoff of context between AI coding agents like Claude Code, Cursor, Codex, and Windsurf with built-in provenance tracking.13,435 npmMIT
- AlicenseAqualityCmaintenanceEnables listing and continuing conversations from Claude Code, Codex, Cursor, and GLM, allowing context handoff between tools by providing historical transcripts as context.5MIT