Skip to main content

The topological memory and architecture layer for AI coding agents.

Project description

Topolox

The topological memory and architecture layer for AI coding agents.

CI Python License: MIT Status

Topolox gives AI coding agents (Claude Code, Cursor) instant, deep understanding of large codebases. Instead of burning tokens reading thousands of files, it feeds an agent exactly the context it needs using an embedded hybrid graph + vector engine — kept live by a background daemon and exposed over MCP and an optional terminal cockpit.

⚠️ Pre-alpha. The scaffold and contracts are in place; the engine is being built phase by phase. See ROADMAP.md.

Why

On a big repo, an AI agent is smart but blind: it either reads dozens of files (slow, expensive) or misses a downstream caller and breaks something. Topolox is the memory + map the agent reads from — deterministic, instantly rebuildable, and zero-token to build.

How it works

discover → parse (multiprocessing tree-sitter) → ParseResult
        → index → Kùzu (graph) + LanceDB (vectors)
        → query (dependencies · context pruner · blast radius)
        → MCP tools  +  CLI  +  Textual TUI
   ┌ watchdog daemon patches the graph live on every file save ┐

Topolox vs. Graphify

Graphify pioneered "drop in a folder, get a knowledge graph." Topolox takes that idea in a different direction: an always-on, agent-native engine for code. They're built for different jobs.

Graphify Topolox
Form factor A Claude Code skill (/graphify) A standalone service: CLI + MCP server + daemon
Graph build AST + LLM extraction (Claude subagents / Gemini) Pure deterministic AST (multiprocessing tree-sitter)
When the LLM runs At build time — spends tokens on every build Only at query time (the consuming agent); build is zero-token
Storage Static graph.json + in-memory NetworkX Embedded Kùzu (graph) + LanceDB (vectors), on disk
Retrieval Lexical substring + IDF + BFS/DFS traversal Vector semantic search + graph traversal (hybrid)
Live updates Opt-in --watch / git hook / manual --update watchdog daemon, ms-level incremental patches
Agent access Optional MCP (7 read-only tools) + Markdown reports MCP-native (4 tools), mcp install for every agent
Inputs Code + docs + papers + images + video Code — 14 languages richly, 300+ at the file level
Signature features Community detection, "god nodes", multi-modal RAG Blast radius, dependency maps, context pruner
Concurrency Single graph, in-memory Multiprocessing + asyncio, embedded DBs

In short: Graphify is a broad, multi-modal, LLM-enriched knowledge-graph builder you invoke as a skill — its graph is richer on inferred relationships. Topolox is a narrow, deterministic, zero-token, always-live code engine that any MCP agent reads from — faster, cheaper, and instantly rebuildable. That's the trade Topolox makes to be an always-on backend.

Two ways to use it

  1. Invisible backend (MCP). Index once, register with your agent, and any MCP client silently pulls grounded, cheap context.
    topolox index .
    topolox mcp install      # registers with Claude Code, Cursor, Codex, Gemini CLI, VS Code, ...
    topolox daemon           # keep the graph live in the background
    
  2. The TUI cockpit (planned — Phase 3). A 3-pane terminal dashboard (agent chat · live knowledge graph · daemon log), topolox ui. See ROADMAP.md.

Supported languages & agents

Languages — symbol + import extraction for Python, JavaScript/JSX, TypeScript/TSX, Go, Rust, Java, C, C++, C#, Ruby, PHP, Kotlin, Swift, and Scala; any other tree-sitter-language-pack grammar (300+) is still parsed and indexed at the file level.

Agentstopolox mcp install registers the MCP server with Claude Code, Cursor, OpenAI Codex CLI, Gemini CLI, VS Code, Windsurf, and Claude Desktop (and any other MCP client — it's a standard stdio MCP server).

Install (from source)

git clone https://github.com/Karnav018/topolox.git
cd topolox
uv sync
uv run topolox --help

Development

uv sync                       # create the env + install dev tools
uv run ruff check .           # lint
uv run ruff format .          # format
uv run mypy src               # type-check (strict)
uv run pytest                 # tests

See CONTRIBUTING.md. Contributions welcome once the engine lands.

Tech stack

Python 3.11+ · Kùzu (graph) · LanceDB (vectors) · tree-sitter (AST) · FastMCP (MCP server) · watchdog (daemon) · Textual (TUI) · Typer (CLI). Optional: fastembed (local embeddings), anthropic (TUI chat).

License

MIT

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

topolox-0.1.0.tar.gz (216.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

topolox-0.1.0-py3-none-any.whl (41.4 kB view details)

Uploaded Python 3

File details

Details for the file topolox-0.1.0.tar.gz.

File metadata

  • Download URL: topolox-0.1.0.tar.gz
  • Upload date:
  • Size: 216.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.19 {"installer":{"name":"uv","version":"0.11.19","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for topolox-0.1.0.tar.gz
Algorithm Hash digest
SHA256 86faa2143e7cecc4fc1844aefd83c2da09a69bc8f8225ce95907f17dd33eafbe
MD5 e105c2589938385631e2030cce438e4c
BLAKE2b-256 484c95d08c5ddb0de80684a64956da41884741793c022eaba8a651bb4189e243

See more details on using hashes here.

File details

Details for the file topolox-0.1.0-py3-none-any.whl.

File metadata

  • Download URL: topolox-0.1.0-py3-none-any.whl
  • Upload date:
  • Size: 41.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: uv/0.11.19 {"installer":{"name":"uv","version":"0.11.19","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}

File hashes

Hashes for topolox-0.1.0-py3-none-any.whl
Algorithm Hash digest
SHA256 48870fc73614a349ef443f7611543387e6b5e75b668359354df1c34d2daba5af
MD5 fbe1900b0e5f711917d6bbd30fa7ff58
BLAKE2b-256 4c325c9a04ea6c1ecf51a474d1bc181fcaf959dbea975867486340fb10b4b454

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page