micro · cc — cognitive compute

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Knowledge work is, by extension, a coding problem.

Frontier models with full system access — shell, filesystem, browser, MCP. Verbose, thorough planning paired with unrestricted file operations lets micro·cc take on complex multi-step work autonomously. Point it at any project directory and go.

Install

pip install micro-cc

Supported platforms: macOS and WSL (Windows Subsystem for Linux) — both are real POSIX/bash environments, which the bash_ tool requires. Terminal keybindings (Shift+Enter, word-jump, etc.) are detected and configured automatically on first run, whatever terminal you're in.

Windows: install WSL first (wsl --install in PowerShell, then reboot), then run pip install micro-cc inside the WSL shell — not in PowerShell/cmd directly. Native Windows isn't supported: there's no bash, and the desktop-control tool depends on macOS-only APIs anyway, so nothing is lost by going through WSL.

Usage

microcc /path/to/your/project

First run, type /login and pick Anthropic, a LiteLLM proxy (Bedrock, Azure, etc.), or Ollama — it writes ~/.micro-cc/.env for you, no manual editing needed.

Controls:

  • Enter — submit · Shift+Enter — newline · Escape — interrupt
  • /login — configure endpoint · /model — switch model · /clear — reset conversation · /keys — store project-scoped secrets · /exit — quit
  • Type / to see the full command list (setup, skills, MCP, headless, batch, etc.)

Headless (-p mode / cron)

microcc-headless /path/to/project_dir "Fix the JWT expiry bug — tokens aren't refreshing correctly."

The microcc equivalent of claude -p — one prompt (argument or piped via stdin), no manifest to write first. project_dir scopes the conversation exactly like the interactive TUI does, so pointing repeated cron runs at the same dir continues that history; a fresh dir starts stateless. Runs fully autonomously (no approval gate), so it never blocks waiting on stdin — a clarifying question from the model is auto-cancelled rather than hung on.

It prints the outcome the same way batch does — STATUS: DONE|NEEDS_INPUT|FAILED — <summary> parsed into a symbol + the full reply:

✓ DONE — Patched JWT expiry check in auth.py

<full reply body, if any, above the status line>

Useful flags: -f/--file (repeatable, points the prompt at specific files), --output-format json (machine-parseable {status, summary, body, project_dir}), --verbose (streams tool calls/results to stderr — handy in cron logs).

Batch (multi-task / cron)

microcc-batch /path/to/base_dir tasks.json

For running several named tasks in one go, each kept in its own isolated subfolder so context never bleeds between them — reach for this over microcc-headless when you want that separation. Each task gets its own subfolder under base_dir — base_dir/{task.name}/ — which is a real project_dir with its own scoped messages.jsonl. Runs are fully autonomous (no approval gate), so a batch never blocks waiting on stdin. To pick a task back up in the full interactive TUI:

cd base_dir/{task.name} && microcc .

Manifest format (tasks.json):

{
  "tasks": [
    {
      "name": "fix-auth-bug",
      "prompt": "Fix the JWT expiry bug — tokens aren't refreshing correctly.",
      "files": ["/absolute/path/to/src/auth.py", "/absolute/path/to/src/middleware.py"]
    },
    {
      "name": "add-tests",
      "prompt": "Add unit tests for the pagination helper."
    }
  ]
}

files is optional and must use absolute paths — cron jobs have no reliable cwd.

Tasks run sequentially. Each is instructed to end its final reply with STATUS: DONE|NEEDS_INPUT|FAILED — <summary>, which the runner parses into a tree view at the end:

/path/to/base_dir
├── ✓ fix-auth-bug         DONE         Patched JWT expiry check in auth.py
├── ? add-tests            NEEDS_INPUT  Which test framework does this repo use?
└── ✓ cleanup-logs         DONE         Removed dead logging branches

2/3 done · 1 need input · 0 failed
cd into: /path/to/base_dir/add-tests  (then `microcc .` to continue)

Only tasks that failed or need input get a cd hint — no need to open every subfolder to check on a large batch.

Data

~/.micro-cc/
  .env                              API keys
  projects/
    {project}_{hash}/
      messages.jsonl                conversation history
      summary.json                  sliding-window summary
      project_path.txt              maps hash back to directory

Tools

Tool Description
bash_ Shell execution in project_dir
read_ Read files with line numbers, offset/limit
write_ Create/overwrite files, auto-creates dirs
edit_ Surgical string replacement (fails if ambiguous)
glob_ Find files by pattern, sorted by mtime
grep_ Regex search with context lines
browser_ Web browsing and page extraction (beta)
computer_use_ Screen interaction and GUI automation (beta)

All tools are discoverable — use search_tools to find more at runtime.

Relative paths resolve to project_dir. Absolute paths work anywhere.

License

Proprietary — all rights reserved. See LICENSE.

Project links

Key dates

PyPI data
Data sourced directly from PyPI's database.
  • Released:
Newer release available (0.2.64)

1 maintainer

PyPI data
Data sourced directly from PyPI's database.
Avatar for georgesalapa from gravatar.com georgesalapa

Credits

Author: George Salapa

License

Copyright (c) 2026 George Salapa. All rights reserved.

Requires

Python >=3.12

Provides Extra

postgres

Report project as malware

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