
Ariadne
io.github.whyy9527Published by GitHub account whyy9527v0.2.2Updated Oct 29, 2026
Deterministic local cross-service API-chain discovery for AI coding agents.
Overview
Local MCP server that indexes the API contract layer of microservice repos so an assistant can trace where an operation lives across services.
- What you can do
- Index the contract layer of configured repos: GraphQL mutations, REST endpoints, Kafka topics and frontend queries
- Query cross-service call chains for an operation name, returning ranked clusters with confidence scores
- Expand a chain and rate results to feed local feedback reranking
- Rescan an indexed workspace when results are flagged as stale
- Run a zero-config demo that clones a public sample stack and prints a real call chain
- When to use it
- Useful when an assistant works in a Spring Boot, TypeScript, FastAPI or Kafka microservice workspace and needs to find which services and contracts a given operation touches, instead of grepping across repos. Best for contract-level lookup rather than general code search.
- Requirements
- Runs as a local stdio process installed from PyPI (ariadne-mcp) with Python 3.10-3.12; needs MCP Python SDK v1 and PyYAML. A config file listing the repo paths to index, and a workspace where the index database is written. The demo clones a public repository into the user's cache directory.
Installation
In SourceWeft
- Open Ariadne in the dashboard and add it to a workspace.
- Enable the server for the chats that should use its tools.
Desktop only via STDIO. STDIO servers start a local process, so they need the SourceWeft desktop host.
Other MCP clients
Follow the launch instructions in the repository.
README
Ariadne
[License: MIT] [MCP] [ariadne MCP server] [Awesome MCP Servers]
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.
[Ariadne demo — scan Spring PetClinic microservices and ask "owner"]
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:
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):
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:
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)
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
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:
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
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:
Run one from a source checkout:
Evaluate ranking
Keep a JSONL judgment list for queries that matter to your workspace:
Run it against a built DB:
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.
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.
Source: README.md at commit 26e4599
Tools
0Version history
4- v0.2.2LatestOct 29, 2026
- v0.2.1Oct 22, 2026
- v0.2.0Oct 12, 2026
- v0.1.3Sep 16, 2026
Score
50% of the applicable checks met
How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.
- Reached in the last 30 days25 pts
Keep the endpoint answering the MCP handshake; SourceWeft probes it every 30 days.
- Auth declared10 pts
Declare the credential headers in the registry entry, or keep the endpoint answering the probe so its auth can be classified.
- Tools listed15 pts
Answer tools/list without a credential, or ship a package that starts in a sandbox without one.
- DescriptionRequired15 pts
- Logo10 pts
- Documentation15 pts
- License10 pts