Why LocalNest?

Every other MCP server forces you to choose: memory or code intelligence. Never both.

LocalNest is the first to combine all three pillars into one server that runs entirely on your machine:

Pillar What it does Why it matters
Code Intelligence Hybrid BM25+vector search, AST-aware chunking, symbol finding (defs/usages/callers) Your AI understands code structure, not just text
Knowledge Graph Temporal entity-triple store with multi-hop traversal and as_of time-travel queries Architectural decisions, dependencies, and facts — versioned over time
Persistent Memory Cross-session recall, semantic dedup, agent-scoped isolation, conversation ingestion Your AI remembers what you taught it — forever

How LocalNest Compares

No other MCP server covers all three pillars. Here's how the landscape breaks down:

vs Memory-Only Servers

LocalNest Mem0 Basic Memory MCP Memory Service AgentMemory
Persistent AI memory Yes Yes Yes Yes Yes
Knowledge graph Yes No No No No
Semantic code search Yes No No No No
Symbol finding (defs/usages) Yes No No No No
AST-aware chunking Yes No No No No
Local-first / no cloud Yes Hybrid Yes Yes Yes
MCP tools 74 8 ~10 24 43

Mem0 has 41k stars and $24M in funding — but it's memory-only with no code intelligence. Basic Memory integrates with Obsidian but can't search code. AgentMemory has auto-capture hooks but zero code features.

vs Code Intelligence Servers

LocalNest GitNexus claude-context codebase-memory-mcp CodeGraphContext
Semantic code search Yes Yes Yes Yes Yes
Knowledge graph Yes Code-only No Code-only Yes
Persistent AI memory Yes No No No No
Cross-session recall Yes No No No No
Symbol finding Yes Yes No Yes Yes
Temporal time-travel queries Yes No No No No
Conversation ingestion Yes No No No No
Local-first / no cloud Yes Yes Partial Yes Yes
MCP tools 74 16 ~5 14 ~10

GitNexus (27k stars) has strong code search but no memory. claude-context (Zilliz, 5.9k stars) is Milvus-backed with no KG or memory. codebase-memory-mcp (DeusData) is the closest competitor — code + KG in a single binary — but has no AI memory layer.

Full Feature Matrix

Feature LocalNest codebase-memory-mcp GitNexus claude-context Basic Memory Mem0
Semantic code search (hybrid BM25+vec) Yes Yes Yes Yes No No
Knowledge graph (entities + triples) Yes Code-only Code-only No No No
Persistent AI memory Yes No No No Yes Yes
Symbol finding (defs/usages/callers) Yes Yes Yes No No No
AST-aware chunking Yes Yes Yes Yes No No
Temporal time-travel queries Yes No No No No No
Multi-hop graph traversal Yes No No No No No
Conversation ingestion Yes No No No No No
Agent-scoped isolation Yes No No No No No
Semantic dedup Yes No No No No No
Hooks system (pre/post callbacks) Yes No No No No No
Interactive TUI dashboard Yes No No No No No
Local-first / no cloud Yes Yes Yes Partial Yes Hybrid
MCP tools 74 14 16 ~5 ~10 8
Zero external deps No (Node.js) Yes (binary) No No No No

LocalNest is the only server that checks every box in the first three rows.

Quick Start

# Install
npm install -g localnest-mcp

# Setup workspace + embeddings
localnest setup

# Verify
localnest doctor

Interactive dashboard:

localnest dashboard

MCP Client Config

After setup, add this to your AI client config:

{
  "mcpServers": {
    "localnest": {
      "command": "localnest-mcp",
      "startup_timeout_sec": 30,
      "env": {
        "MCP_MODE": "stdio",
        "LOCALNEST_CONFIG": "~/.localnest/config/localnest.config.json",
        "LOCALNEST_INDEX_BACKEND": "sqlite-vec",
        "LOCALNEST_MEMORY_ENABLED": "true"
      }
    }
  }
}

Works with Claude Code, Cursor, Windsurf, Cline, Continue, Gemini CLI, and any MCP-compatible client.

Tool Suites

LocalNest exposes 74 specialized MCP tools, organized into focused suites:

Full parameter reference: Tool Documentation

Agentic Workflows

LocalNest is designed as the foundational context layer for AI coding agents:

  • Cold start — agent_prime instantly hydrates the context window with relevant memories, recent changes, and project state.
  • Deep investigation — find runs fused search across code fragments and historical design decisions in a single call.
  • Continuous learning — teach saves architectural rules that persist across sessions, ensuring agents never repeat mistakes.
  • Outcome capture — capture_outcome records what worked and what didn't, building an experience base over time.

Enterprise-Grade Quality

  • OIDC Trusted Publishing for verifiable npm provenance
  • Continuous CodeQL static analysis on all branches
  • OpenSSF Scorecard monitoring and proactive Dependabot updates

Troubleshooting

Direct npm install -g git+https://... may fail with TAR_ENTRY_ERRORS. This is a known npm limitation.

Fix: clone, pack, install

git clone https://github.com/wmt-mobile/localnest.git
cd localnest && npm pack
npm install -g ./localnest-mcp-*.tgz

cd $(npm root -g)/localnest-mcp && npm install --no-save @huggingface/transformers
localnest doctor

Resources