Locally stores and retrieves coding context with SQLite, hybrid search, session hooks, and MCP tools.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent ā or use 1-click editor setup below.
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š” Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Agentkits Memory.
The aitytech/agentkits-memory MCP server adds persistent memory to AI coding workflows. It stores memories, sessions, observations, and embeddings in a local SQLite database, typically at .claude/memory/memory.db. Stored information can include architectural decisions, recurring code patterns, error resolutions, file activity, and summaries from earlier sessions.
The system is designed for coding assistants that otherwise lose context when a session ends. On a later session, relevant history can be injected automatically, and the assistant can query the database through MCP instead of relying on manually maintained notes. A browser-based viewer is also available for browsing, searching, creating, editing, and deleting memories.
Hooks capture session events, tool activity, decisions, and summaries while work is in progress. Background workers can enrich observations with generated summaries, create local vector embeddings, compress older data, and archive or clean up historical sessions. These tasks run asynchronously rather than blocking the main coding interaction.
Search uses multiple layers. Full-text indexing supports direct term matching through SQLite FTS5, while sqlite-vec and a local multilingual-e5-small ONNX model support semantic similarity across more than 100 languages. A progressive retrieval flow can begin with a compact search result, continue to timeline context, and fetch full details only when needed.
The aitytech/agentkits-memory MCP server does not require a database daemon. Data remains on the local machine, and the README states that no cloud account, external API key, or paid service is required. Hooks are short-lived processes, while worker processes have timeout, locking, signal-handling, and cleanup behavior described by the project.
The package provides an automated setup command:
It detects supported environments and configures the MCP server, platform-specific hooks or rules, and the embedding model. Platform selection can be explicit:
The documented integrations include Claude Code, Cursor, Windsurf, Cline, and OpenCode. Claude Code also has a plugin-marketplace installation path that adds the hooks, MCP server, and memory workflow skill. The web viewer starts with:
After starting it, open http://localhost:1905. The project does not list environment variables or credential configuration as required setup.
The MCP interface exposes nine listed operations:
Additional capabilities include automatic context capture, multilingual local vector search, memory namespaces and tags, session timelines, JSON export and import, and lifecycle management for older data. The web viewer provides management controls separate from the MCP tools.
This project is aimed at local coding-assistant memory rather than a hosted, shared memory service. Its data is stored in a local SQLite file, so synchronization between machines or users is not described. Semantic search depends on the locally downloaded embedding model. The README states that background processing performs AI enrichment, but it does not identify an external model provider or require an API key.
The documented client list is broader than the four clients commonly used for MCP directory compatibility: Claude Code, Cursor, Windsurf, Cline, and OpenCode are named explicitly. Other MCP clients may work, but the supplied material does not provide client-specific configuration details for them.
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