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Your codebase as a queryable graph

Built for AI agents. Precomputed answers about symbols, dependencies, and call graphs — no source reading required.

npm install -g @kehl-io/nestweaver

The problem

Every AI session starts the same way: your agent reads dozens of files, burns thousands of tokens on boilerplate, and still misses the three functions that matter.

The re-explain tax: you re-describe your codebase structure every session because nothing persists. Your agent has no memory of how things connect.

NestWeaver builds a persistent knowledge graph that gives your agent precomputed answers — not raw files.

How it works

1

Index

Parse your codebase into a queryable graph. 32 languages via Tree-sitter with cross-file symbol resolution.

2

Query

Ask structural questions: callers, dependencies, blast radius, type usage. The graph knows how everything connects.

3

Context

Personalized PageRank extracts only task-relevant symbols within a token budget. Your agent gets exactly what it needs.

4

Connect

40 MCP tools let any AI agent query the graph directly. Works with Claude Code, Cursor, Aider, and more.

Token efficiency by design

Input tokens are 85-95% of AI coding bills. NestWeaver is designed to minimize every query.

Without NestWeaver

  • Agent reads 30 files to find 3 relevant functions
  • Re-explains codebase structure every session
  • No structural understanding — just text similarity
  • Burns tokens on boilerplate, imports, comments

With NestWeaver

  • Set a token budget — the graph fills it with the right context
  • Persistent graph eliminates the re-explain tax
  • PageRank ranks by structural relevance, not just keywords
  • Returns symbols and relationships — precomputed answers

Benchmarked Against the Competition

Measured against Graphify and GitNexus across 4 open-source repos on Apple M3 Pro.

17-34x
Faster Queries
vs Graphify on repos with 14K-44K files
632ms
Incremental Re-index
after a single file change (Tailwind CSS)
14.8M
Edges Extracted
Elasticsearch — 511K symbols in one graph
Repository NestWeaver Graphify GitNexus
Tailwind CSS 542 files 157ms 185ms 700ms
Deno 14,136 files 82ms 1,355ms 908ms
Next.js 29,402 files 71ms 2,440ms 1,116ms
Elasticsearch 43,806 files 617ms crashed 1,573ms

Speed without accuracy is meaningless

NestWeaver — 30 connected symbols per query, ranked by PageRank, with full function signatures and cross-file relationships

Graphify — Returns file-level nodes, but 9-15% are garbage stubs (vitest config, node_path, etc.) with no relevance ranking

GitNexus — Finds symbol definitions but returns 0 callers, 0 callees — locates code without explaining how it connects

Features

Languages

Tree-sitter parsing with cross-file symbol resolution and confidence scoring.

MCP Tools

Plug into Claude Code, Cursor, Aider, Copilot, and any MCP-compatible agent.

PageRank Extraction

Token-budget-aware context selection via Personalized PageRank. Get exactly what matters.

Semantic Search

Natural language queries with local BERT embeddings. Metal-accelerated on Apple Silicon.

Brain Integration

Link Obsidian vaults and architecture docs to code symbols. Query both in one graph.

One-Command Setup

nestweaver setup auto-configures 16 AI tools in one command.

Web UI

GPU-rendered interactive graph visualization. Explore your codebase visually.

Open Source

Single Rust binary. MIT license. Local-first by default. No vendor lock-in.

Works with the agents you already use

NestWeaver isn't a competing agent — it's infrastructure that makes existing agents smarter. Add it as an MCP server and your agent instantly gains structural code understanding.

OpenClaw

Local-first AI assistant

OpenClaw connects to 22+ messaging platforms and routes conversations through configurable LLM backends. It supports MCP natively — add NestWeaver as a server and every conversation gains structural code intelligence.

Replace grep-then-read chains with single graph queries
Reduce context compaction triggers by loading less raw code
Persistent graph eliminates per-session codebase re-discovery
View on GitHub

HermesAgent

Self-improving coding agent

HermesAgent by Nous Research is a model-agnostic coding agent that learns from experience. Its MCP client auto-discovers NestWeaver's 40 tools at startup — giving the agent structural code understanding it can't get from grep and file reads alone.

Answer "what calls this?" from the graph instead of reading 10+ files
Eliminate the 4-identical-reads block by providing the right context first
Get function + callers + dependencies in ~400 tokens instead of ~8,000
View on GitHub

Zero code changes required

Any MCP-compatible agent can use NestWeaver as a code intelligence backend. Index your codebase once, add NestWeaver as an MCP server, and your agent's next session starts with structural understanding instead of blind file reading.

nestweaver setup # auto-configures 16 AI tools including MCP servers

NestWeaver is compatible with any agent that supports the Model Context Protocol. Project names and logos are trademarks of their respective owners.

Get started

Install

npm (recommended)

npm install -g @kehl-io/nestweaver

Cargo

cargo install nestweaver

Or download pre-built binaries for macOS and Linux, including NestWeaver.app for macOS.

Setup + first index

nestweaver setup # configures 16 AI tools
nestweaver index . # parses your codebase