pip install cognis-apidiff
apidiff scan . # → prioritized findings in secondsapidiff detects breaking changes between two OpenAPI / GraphQL definitions.
- Install:
pip install -e . - Diff a baseline against a candidate definition:
apidiff diff openapi.old.yaml openapi.new.yaml
- Force the format when auto-detection is ambiguous:
apidiff diff schema.old.graphql schema.new.graphql --fmt graphql
- Read the output as JSON for tooling:
apidiff diff openapi.old.yaml openapi.new.yaml --format json
- Automate in CI —
--fail-oncontrols when the diff returns a non-zero exit:apidiff diff openapi.old.yaml openapi.new.yaml --fail-on breaking
- Why apidiff? · Features · Quick start · Example · Architecture · AI stack · How it compares · Integrations · Install anywhere · Related · Contributing
API teams catch breaks in CI
apidiff is single-purpose, scriptable, and self-hostable: point it at a target, get prioritized results in the format your workflow already speaks (table · JSON · SARIF), gate CI on it, and let agents drive it over MCP.
- ✅ Detect Format
- ✅ Diff Openapi
- ✅ Diff Graphql
- ✅ Diff Files
- ✅ Runs on Linux/macOS/Windows · Docker · devcontainer
- ✅ Ports in Python, JavaScript, Go, and Rust (
ports/)
pip install cognis-apidiff
apidiff --version
apidiff scan . # scan current project
apidiff scan . --format json # machine-readable
apidiff scan . --fail-on high # CI gate (non-zero exit)$ apidiff scan .
[HIGH ] API-001 example finding (./src/app.py)
[MEDIUM ] API-002 another signal (./config.yaml)
2 findings · risk score 5 · 38ms
flowchart LR
IN[input] --> P[apidiff<br/>analyze + score]
P --> OUT[report]
apidiff is interoperable with every popular way of using AI:
- MCP server —
apidiff mcp(Claude Desktop, Cursor, Cognis.Studio, uncensored-fleet) - OpenAI-compatible / JSON — pipe
apidiff scan . --format jsoninto any agent or LLM - LangChain · CrewAI · AutoGen · LlamaIndex — wrap the CLI/JSON as a tool in one line
- CI / scripts — exit codes + SARIF for non-AI pipelines
| Cognis apidiff | oasdiff | |
|---|---|---|
| Self-hostable, no account | ✅ | varies |
| Single command, zero config | ✅ | |
| JSON + SARIF for CI | ✅ | varies |
| MCP-native (AI agents) | ✅ | ❌ |
| Polyglot ports (JS/Go/Rust) | ✅ | ❌ |
| Open license | ✅ COCL | varies |
Built in the spirit of oasdiff, re-framed the Cognis way. Missing a credit? Open a PR.
Pipes into your stack: SARIF for code-scanning, JSON for anything, an MCP server (apidiff mcp) for AI agents, and a webhook forwarder for SIEM/Slack/Jira. See docs/INTEGRATIONS.md.
pip install "git+https://github.com/cognis-digital/apidiff.git" # pip (works today)
pipx install "git+https://github.com/cognis-digital/apidiff.git" # isolated CLI
uv tool install "git+https://github.com/cognis-digital/apidiff.git" # uv
pip install cognis-apidiff # PyPI (when published)
docker run --rm ghcr.io/cognis-digital/apidiff:latest --help # Docker
brew install cognis-digital/tap/apidiff # Homebrew tap
curl -fsSL https://raw.githubusercontent.com/cognis-digital/apidiff/main/install.sh | sh| Linux | macOS | Windows | Docker | Cloud |
|---|---|---|---|---|
scripts/setup-linux.sh |
scripts/setup-macos.sh |
scripts/setup-windows.ps1 |
docker run ghcr.io/cognis-digital/apidiff |
DEPLOY.md (AWS/Azure/GCP/k8s) |
mcpforge— Scaffold, test, and publish MCP servers in minutespromptlint— Lint, version, and test prompts as code with a CI gateenvdoctor— .env validator, secret-presence and config-drift checkercodeglance— Repo onboarding map — architecture + hotspots for humans and agentsflakefinder— Flaky-test detector from CI history with quarantine suggestionslicenselens— Dependency license + SBOM gate, developer-CLI first
Explore the suite → 🗂️ all 170+ tools · ⭐ awesome-cognis · 🔗 cognis-sources · 🤖 uncensored-fleet · 🧠 engram
PRs, new rules, and demo scenarios are welcome under the collaboration-pull model — see CONTRIBUTING.md and SECURITY.md.
{} composes with the 300+ tool Cognis suite — JSON in/out and a shared
OpenAI-compatible /v1 backbone. See INTEROP.md for the
suite map, composition patterns, and reference stacks.
Source-available under the Cognis Open Collaboration License (COCL) v1.0 — free for personal, internal-evaluation, research, and educational use; commercial / production use requires a license (licensing@cognis.digital). See LICENSE.