Ariadne

Name: Ariadne
Author: whyy9527

by whyy9527version 0.2.2i★ –iRuns on your computer

Registry nameio.github.whyy9527/ariadne

Install

Overview

Description from the maker (original English)

Deterministic local cross-service API-chain discovery for AI coding agents.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiVery new↓ 111/wk · ★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Developer tools

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
The registry lists no key to fill in.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "ariadne": {
      "command": "uvx",
      "args": [
        "ariadne-mcp"
      ]
    }
  }
}

Run this in your terminal

claude mcp add ariadne -- uvx ariadne-mcp

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "ariadne": {
      "command": "uvx",
      "args": [
        "ariadne-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "ariadne": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "ariadne-mcp"
      ]
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account whyy9527, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Developer toolsi

More stars than 0% of the other 5554 servers in this category
Published to the registry more recently than 67% of the other 5554 servers in this category
Basic checks equal to or better than 100% of the other 5554 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is Ariadne safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

The registry does not list a required key, though some servers ask you to sign in on first use.

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.2.2) reached the registry 12 days ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: GitHub, Desktop Commander, Cloudflare MCP

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

GitHub

GitHub’s official server lets AI read and manage code, issues and pull requests in your account. Use GitHub’s hosted version or run it locally with Docker.

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Computer or cloud

Install

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Cloudflare MCP

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Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

Ariadne

Ariadne's thread — a way out of the microservice maze.

Cross-service API dependency graph for Spring Boot + TypeScript microservice stacks. MCP stdio server for AI coding assistants (Claude Code, Cursor, Windsurf), with a CLI twin. Local SQLite + TF-IDF. Zero ML dependencies.

70-second deterministic terminal walkthrough. Reproduce it from docs/demo.tape.

What it does

Indexes the *contract layer* — GraphQL mutations, REST endpoints, Kafka topics, frontend queries. Nothing else. That's why results fit an AI context window.

Ask Claude *"where does createOrder live across the stack?"* and query_chains returns:

Top Cluster #1  [confidence: 0.91]

Services: gateway, orders-svc, billing-svc, web

[web] Frontend Mutation: createOrder
[gateway] GraphQL Mutation: createOrder
[orders-svc] HTTP POST /orders: createOrder
[orders-svc] Kafka Topic: order-created
[billing-svc] Kafka Listener: order-created → chargeCustomer

The response is intentionally bounded for an AI context window. See the reproducible public-stack benchmark for measured retrieval, serialized token, and timing results against rg and grep.

Current public-stack benchmark (48 reviewed queries across Spring REST, GraphQL/TypeScript, Kafka, and FastAPI):

Backend	Top-1	Top-3	MRR	Warm query	Mean output
Ariadne	89.6%	95.8%	0.927	<0.4 ms	375 tokens
`rg`	37.5%	56.2%	0.510	~9 ms	591 tokens
`grep`	37.5%	56.2%	0.510	~9 ms	591 tokens

Full methodology and per-stack results · raw JSON evidence

This corpus is operation-name-heavy and measures deterministic contract lookup compatibility. It is not yet a natural-language relevance benchmark.

Reproduce the measurements with uv:

uv run --locked --extra benchmark python benchmarks/run.py

The first run that uses tiktoken downloads its encoding data and needs network access. The benchmark also calls the system git, rg, and grep commands.

Supports: GraphQL · Spring HTTP/Kafka/RestClient · Python FastAPI · TypeScript Apollo/fetch/axios · Cube.js.

Try it in 30 seconds (zero config)

pip install ariadne-mcp

ariadne-mcp demo

Clones spring-petclinic-microservices into ~/.cache/ariadne-mcp/demo, scans it, and prints the top cluster for owner — a real cross-service call chain. No config file, no workspace setup.

Did Ariadne find the chain you expected? Share one minute of structured feedback. Ariadne sends no usage data automatically; the form opens only when you choose to submit it.

Install on your own workspace

pip install ariadne-mcp

cp "$(python -c 'import ariadne_mcp, os; print(os.path.join(os.path.dirname(ariadne_mcp.file), "ariadne.config.example.json"))')" ariadne.config.json

edit ariadne.config.json (list the repos you want indexed)

ariadne-mcp install ariadne.config.json ~/your-workspace

Restart Claude Code. install is idempotent — re-run after pulling new code, or let the assistant call rescan on a stale_warning.

Run an MCP server from a source checkout

Prepare the environment with the project's pinned uv version, then configure the MCP client to launch that environment's Python directly:

cd /path/to/ariadne

uv sync --locked --no-dev --inexact .venv/bin/python -m ariadne_mcp.server \ --db /path/to/workspace/.ariadne/ariadne.db \ --fb /path/to/workspace/.ariadne/feedback.db

Use an absolute interpreter path in the MCP client configuration. Run the sync step after dependency changes; it is separate from the long-running server. --inexact preserves other installed dependency groups in a development checkout. If UV_PROJECT_ENVIRONMENT selects another environment, configure that environment's Python instead of .venv/bin/python.

With the project's pinned uv version, wrapping a long-running server in uv run keeps uv's shared package-cache lock held for the server's lifetime, which prevents normal uv cache prune. A direct Python launch avoids that lock. Separate stdio client connections can run separate server processes.

After your first real query, you can optionally send closed-ended usage feedback. No source, query, or usage data is transmitted by Ariadne itself.

Config

{ "repos": [

{ "path": "../gateway" }, { "path": "../orders-svc" }, { "path": "../web" } ]}

Scanners are inferred from each repo's top-level files (pom.xml / build.gradle / package.json / SDL). See docs/CONFIG.md for the detection table and override syntax.

Reproducible public samples

Each sample pins an upstream commit, scans real service source, runs one query, and verifies manually reviewed node IDs:

Example	Contract path
`spring-petclinic`	Spring REST gateway → service
`one-platform`	GraphQL/TypeScript services
`kafka-microservices`	Kafka producer → consumer
`fastapi-microservices`	Python FastAPI routes

Run one from a source checkout:

python examples/run.py kafka-microservices

Evaluate ranking

Keep a JSONL judgment list for queries that matter to your workspace:

{"hint":"createOrder","expected_node_ids":["gateway::gql::m::createOrder"],"k":3}

{"hint":"owner","expected_node_ids":["customers::http::GET /owners/{ownerId}"],"match":"any","k":5}

Run it against a built DB:

ariadne-mcp --db .ariadne/ariadne.db eval eval/queries.jsonl --top 3 --min-hit-rate 0.8

The command evaluates top-k hit rate and MRR using a stable internal candidate depth, and exits non-zero when a configured threshold fails. Add --feedback-db .ariadne/feedback.db to include local feedback reranking in the eval.

Architecture, MCP tools, scoring math, feedback boost → docs/ARCHITECTURE.md. Custom scanners (Go, Rust, anything) → docs/CUSTOM_SCANNERS.md. Maintainer adoption snapshots → docs/ADOPTION_METRICS.md.

Business acceptance and ablation

The source-backed business suite covers all nine built-in scanners and the complete MCP query/expand/rate/rescan lifecycle, including a real stdio client. It uses synthetic contracts; private workspace sources and feedback stay local.

uv sync --locked --extra benchmark --group dev

uv run --locked --extra benchmark --group dev python -m pytest tests/ -q uv run --locked --extra benchmark python benchmarks/ablation.py \ --output benchmarks/.work/ablation.json

See quality experiment results for the fixed-input baseline, component ablations, output costs and remaining limitations. The server supports Python 3.10, 3.11, and 3.12. Runtime requirements are MCP Python SDK v1 (mcp>=1,<2) and PyYAML (PyYAML>=6,<7); tiktoken is an optional benchmark dependency. uv.lock pins the maintainer and CI environment and does not constrain dependencies resolved by package users.

Ariadne

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Developer toolsi

Common questions

Alternatives

GitHub

Desktop Commander

Cloudflare MCP

README from the maker

Ariadne

What it does

Try it in 30 seconds (zero config)

Install on your own workspace

edit ariadne.config.json (list the repos you want indexed)

Run an MCP server from a source checkout

Config

Reproducible public samples

Evaluate ranking

Business acceptance and ablation