CodeAbra/iai-mcp

Overview

An open-source memory system designed to provide persistent context for AI coding assistants. It is benchmarked as the top performer among similar tools and implemented in Python.

Best for

Best for
Developers using AI coding assistants who need reliable, persistent memory across sessions

Use cases

• Give coding assistants long-term memory across multiple sessions
• Store project-specific context for AI code generation
• Integrate with MCP-compatible development tools and editors

How to use

Install

pip install iai-pme

Tools exposed

• memory_recall
• memory_temporal_recall
• memory_recall_structural
• memory_search
• memory_capture
• memory_contradict
• memory_reinforce
• memory_consolidate
• profile_get_set
• Store-direct
• IAI_MCP_STORE
• IAI_MCP_PYTHON
• IAI_MCP_RECALL_CONCURRENCY
• IAI_MCP_RECALL_SLOT_WAIT_SEC
• IAI_MCP_EMBED_PROVIDER
• IAI_MCP_EMBED_URL
• IAI_MCP_EMBED_DIM
• IAI_MCP_EMBED_MODEL_ID
• IAI_MCP_EMBED_TIMEOUT_SEC

Tested with

Claude Desktop, Claude Code, Cursor, Cline, Continue

Notes

An open-source memory system designed to provide persistent context for AI coding assistants. It is benchmarked as the top performer among similar tools and implemented in Python.

133 stars on GitHub. Last updated 2026-05-15. Licensed MIT.

Use cases

• Give coding assistants long-term memory across multiple sessions
• Store project-specific context for AI code generation
• Integrate with MCP-compatible development tools and editors

Pros

• Top benchmarked performance among open-source memory systems
• Lightweight Python implementation with clear codebase
• Actively developed with 133 GitHub stars

Cons

• Relatively small community compared to larger tools
• Requires manual setup and integration into existing workflows
• Primarily focused on AI coding assistants, not general-purpose memory

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.