ContextBridge MCP Server

MCP memory server for AI coding assistants. Windows Service, ONNX embeddings, SQLite vector search.

Local serverstdioPython

What is the ContextBridge MCP Server?

MCP memory server for AI coding assistants. Windows Service, ONNX embeddings, SQLite vector search.

What it actually does

A zero-dependency MCP memory server for Windows that gives AI coding assistants a shared, persistent memory layer with semantic search.

AI coding assistants like Claude Code are stateless—each session starts fresh, with no persistent memory of your prior context, decisions, or discoveries. ContextBridge solves this by running as a background Windows Service that all your AI tools connect to. It stores memories persistently, searchable by meaning (not keywords), so context accumulates across sessions and across different tools simultaneously.

  • Zero external dependencies — — No Docker, Postgres, Python, or Ollama. Everything runs in one Windows Service process
  • In-process embeddings — — Embedding model (all-MiniLM-L6-v2, ~22 MB) runs via ONNX Runtime; no external API calls
  • Single-file storage — — SQLite database at %ProgramData%\ContextBridge\memories.db. Backup is one file copy
  • Shared across tools — — Claude Code (HTTP), Claude Desktop (stdio), Cline, VS Code Chat Agents all connect to the same memory store in real-time
  • Memory survives service restarts — — Memories persist in SQLite; the embedding model loads once on startup and stays warm

Configuration

  • Windows 10 / Windows 11 (required for Windows Service integration) - Option A: .NET 10 SDK (if installing via dotnet tool) - Option B: Windows 10+ (no additional prerequisites if downloading a pre-built .exe) - Admin PowerShell (required to install/uninstall the Windows Service)

More MCP options

Compare MCP servers by category, or browse hosted MCP servers if you prefer an endpoint over a local process.

Maintainer setup documentation.

Recorded tools

Check the linked publisher documentation and your connected client's tool list. Names and availability can vary with the server version and account permissions.

ToolWhat it does
project<repo-name> — scope memories to a project
typedecision — architectural or technology choices
contentthe session summary (free-form text)
ttl_dayshow many days to keep the handoff before auto-expiry (default: 7)
memory_writeStore a single memory with automatic semantic embedding and optional tags
memory_batch_writeStore multiple related memories atomically (efficient end-of-session extraction)
memory_searchSemantic search — natural language query, returns nearest-neighbor results
memory_listPaginated list of all memories with optional tag filters
memory_updateUpdate a memory's content (re-embedded automatically)
memory_deleteDelete a memory by ID
memory_statusService health check, record count, model info
handoff_writeCapture session state — what you're working on, decisions made, next steps
handoff_listRetrieve active handoffs, optionally filtered by project
handoff_acknowledgeRemove a handoff after processing it (permanent deletion)

Configuration

  • Windows 10 / Windows 11 (required for Windows Service integration) - Option A: .NET 10 SDK (if installing via dotnet tool) - Option B: Windows 10+ (no additional prerequisites if downloading a pre-built .exe) - Admin PowerShell (required to install/uninstall the Windows Service)

Example prompts to try

  • “Use ContextBridge to project.”
  • “Use ContextBridge to type.”
  • “Use ContextBridge to content.”

Frequently asked questions

MCP memory server for AI coding assistants. Windows Service, ONNX embeddings, SQLite vector search. Confirm the tools offered by your installed version in the connected client. Tool availability and permissions depend on the server and account configuration.