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0.2.0

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agentmap-scan

Map every AI API call in a codebase — offline, no LLM, no keys. Opens a webpage of your providers, models, and agents.

agentsanthropicllmobservabilityopenaiscanner
Published20 Aug 2026
Direct dependencies1
Transitive dependenciesNot calculated

README

Version 0.2.0 documentation

agentmap

Map every AI API call in a codebase — offline, no LLM, no API keys. Run one command and get a webpage showing which files call which providers, what models you use, and what each agent is responsible for.

pip install agentmap-scan
cd your-project
agentmap

A browser page opens with four sections:

  • Calls by file — every AI API call site, file:line, provider-tagged.
  • Providers & models — the distinct providers and model names in use, with counts.
  • Agents & responsibilities — each agent's name and what its system prompt says it does.
  • Routing — the env vars to send those calls through a gateway.

How it works

Pure regex over your source — it matches provider endpoint hosts (api.openai.com, api.anthropic.com, …) and SDK call signatures (.chat.completions.create, .messages.create, …), so it finds calls in Python, JS/TS, Go, Rust, Ruby, PHP, Java, shell/curl — not just the official SDKs. Agent responsibilities come straight from the system prompts in your code, trimmed to one line. Nothing leaves your machine.

Detects 20 providers: OpenAI, Anthropic, Google Gemini/Vertex, Azure OpenAI, DeepSeek, Groq, xAI, Mistral, Cohere, Bedrock, Together, Fireworks, OpenRouter, Perplexity, Replicate, Hugging Face, Ollama, LiteLLM, LangChain.

Commands

agentmap [PATH]              # scan + open the report (default: current dir)
agentmap --no-open PATH      # scan, write the HTML, don't launch a browser
agentmap install PATH        # write .env.agentmap routing env vars
agentmap install PATH --auto # also rewrite hardcoded provider base_urls in place

Routing → save money

agentmap install writes the env vars that point your OpenAI/Anthropic-compatible calls at a gateway. Point them at Brevitas to compress context losslessly and cut your token bill:

agentmap install . --target http://localhost:4242
source .env.agentmap

Limitations (honest)

Agent detection is a heuristic. It reliably catches raw OpenAI/Anthropic message dicts, system=/system_prompt=/instructions= assignments (incl. X_system, X_PROMPT names), CrewAI Agent(role=…), and .agent("name") calls. It does not yet understand graph frameworks (LangGraph node graphs, AutoGen). PRs adding per-framework matchers welcome.

License

MIT.

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Declared dependencies 1

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1 direct targetsNot calculated transitive count
Package / targetRequirementRelationship
click
Environment
{
  "extras": "",
  "marker": null,
  "requires_python": ">=3.10",
  "evaluation": "NOT_EVALUATED"
}
click>=8.1.0runtime

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agentmap_scan-0.2.0-py3-none-any.whl

bdist_wheel · 16.61 KB · Python py3

Source file
agentmap_scan-0.2.0.tar.gz

sdist · 30 KB · Python source

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brevitas-ai/agentmap

Shared repository data · GitHub

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Observed since 20 Oct, 22:39 UTC

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package_version:abd8ef2ef1a479672bffa80dac0435df786b76e4eaf933aacc6e1e0fbf5b8467

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