Skip to main content
Glama
DIP-RO
by DIP-RO

Promem-MCP

Project Memory MCP — persistent project context for AI coding agents. Built by DIP-RO.

pip install promem-mcp

No database. No cloud. No daemon. No manual memory management.

ContextMCP is a local-first, MCP-native context runtime that gives AI coding agents persistent project understanding — architecture, rules, decisions, conventions, environment intelligence, and Git context — without repeated explanations or context waste.

Quick Start

pip install promem-mcp

Then register ContextMCP with your AI coding client:

# See which clients are detected
promem config

# Auto-configure a specific client (with backup + merge)
promem config cursor
promem config claude-code
promem config claude-desktop
promem config vscode

Or manually add to your client's MCP config:

{
  "mcpServers": {
    "contextmcp": {
      "command": "contextmcp",
      "args": []
    }
  }
}

VS Code note: VS Code uses "servers" key, not "mcpServers". Run promem config vscode for the correct format.

That's it. Your AI coding agent now has persistent project context.

How It Works

How It Works

Features

  • Zero-setup storage — SQLite database created automatically in OS-appropriate directory

  • Automatic project detection — language, framework, package manager, test framework

  • Persistent memory — rules, decisions, conventions, environment facts, Git intelligence

  • Token-efficient retrieval — FTS5 search with token budgeting, returns only relevant context

  • Provenance tracking — every memory knows where it came from and how confident it is

  • Secret redaction — API keys, tokens, passwords are never stored or returned

  • Project isolation — project memories never leak across projects

  • Stale context detection — flags memories that conflict with current project state

  • Contradiction detection — identifies conflicting project rules

  • Session continuity — handoff summaries for switching between agents/sessions

  • Git intelligence — recent commits, changed files, TODOs/FIXMEs

  • Environment diagnostics — Python version, venv, .env completeness, Docker

  • Local-first — no network requests, no cloud, no external services

MCP Tools

Tool

Description

ctx_search

Search persistent project context with token budget

ctx_get

Get a specific memory by ID

ctx_save

Save a memory, decision, rule, or fact

ctx_update

Update an existing memory

ctx_delete

Delete a memory

ctx_project

Get current project information

ctx_rules

Get all project rules and conventions

ctx_decisions

Get all technical/architecture decisions

ctx_recent

Get recent memories and latest session

ctx_git

Get Git intelligence

ctx_environment

Get environment intelligence

ctx_diagnostics

Run environment diagnostics

ctx_summary

Get compact project summary for handoff

CLI

contextmcp --version        # Version
promem status           # Project + storage status
promem doctor           # Health checks
promem stats            # Usage statistics
promem search "query"   # Search context
promem memory list      # List memories
promem decision "text"  # Save a decision
promem privacy          # Privacy info
promem config           # Client configuration
promem repair           # Rebuild index, optimize DB
promem reset            # Delete all data (with confirmation)

Client Support

Client

Auto-config?

Config Key

Claude Code

promem config claude-code

mcpServers

Claude Desktop

promem config claude-desktop

mcpServers

Cursor

promem config cursor

mcpServers

VS Code / Copilot

promem config vscode

servers

OpenCode

promem config opencode

mcp

Gemini CLI

promem config gemini-cli

mcpServers

Windsurf

promem config windsurf

mcpServers

Cline

promem config cline

mcpServers

Roo Code

promem config roo-code

mcpServers

Amazon Q

promem config amazon-q

mcpServers

ZCode (GLM/Zhipu)

promem config zcode

mcpServers

Tabnine

promem config tabnine

mcpServers

No client supports true zero-config auto-registration. ContextMCP detects installed clients, offers to write config (with backup + merge), and provides exact copy-paste snippets.

Privacy

  • Local only — no network requests

  • Project contents not uploaded

  • Secrets redacted — never stored or returned

  • No cloud dependencies

promem privacy

Storage Location

ContextMCP uses project-local storage — no centralized OS directory, no wasted space.

Location

Path

Project-local (default)

<project-root>/.contextmcp/

Each project gets its own .contextmcp/contextmcp.db. Storage travels with the project. No global storage bloat.

Add .contextmcp/ to your .gitignore (already included by default in ContextMCP's ignore patterns).

Override with CONTEXTMCP_DATA_DIR environment variable if needed.

Installation

# pip
pip install promem-mcp

# uv
uv add contextmcp

# pipx (global CLI)
pipx install contextmcp

Works in venv, virtualenv, uv, pipx, and system Python.

Development

git clone https://github.com/contextmcp/contextmcp.git
cd contextmcp
pip install -e ".[dev]"
pytest

License

MIT

-
license - not tested
-
quality - not tested
A
maintenance

Maintenance

Maintainers
Response time
0dRelease cycle
3Releases (12mo)
Commit activity

Resources

Unclaimed servers have limited discoverability.

Looking for Admin?

If you are the server author, to access and configure the admin panel.

Related MCP Connectors

  • The project brain for AI coding agents — memory, decisions, sprints, knowledge base via MCP.

  • Persistent memory and cross-session learning for AI coding assistants (hosted remote MCP).

  • Give your AI agent a persistent map of your project's structure, dependencies, and bugs.

View all MCP Connectors

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/DIP-RO/MCP_Package'

If you have feedback or need assistance with the MCP directory API, please join our Discord server