# Option A: Gitea Personal Access Tokens (Recommended)
GITEA_TOKEN_DADESCHOOLS="your_token_here"
GITEA_TOKEN_PRGS="your_token_here"

# Option B: Gitea Username & Password (fallback)
GITEA_USER_DADESCHOOLS="username"
GITEA_PASS_DADESCHOOLS="password"
GITEA_USER_PRGS="username"
GITEA_PASS_PRGS="password"

# Optional: Fallback to macOS Keychain (via git credential fill)
# GITEA_USE_KEYCHAIN=1

MCP Server (Recommended)

The Gitea-Tools MCP server exposes all functionality as structured tool calls. Any MCP-compatible agent (Antigravity, Claude Code, etc.) can call these tools natively.

Available Tools

Tool	Description
`gitea_create_issue`	Create an issue with title, body, remote
`gitea_create_pr`	Open a pull request with title, head, base
`gitea_close_issue`	Close an issue by number
`gitea_list_issues`	List issues with state/label filters
`gitea_view_issue`	Get full details of a single issue
`gitea_mark_issue`	Claim/release an issue (start/done)
`gitea_mirror_refs`	Mirror branches + tags between instances

Setup

1. Install dependencies

cd /Users/jasonwalker/Development/Gitea-Tools
python3 -m venv venv          # skip if venv already exists
source venv/bin/activate
pip install "mcp[cli]"

2. Configure your AI client

The MCP server uses stdio transport — each client starts it as a subprocess. Add the config below to your client, then restart it.

Antigravity (Google)

Add to ~/.gemini/antigravity-ide/mcp_config.json inside "mcpServers":

"gitea-tools": {
  "command": "/Users/jasonwalker/Development/Gitea-Tools/venv/bin/python3",
  "args": ["/Users/jasonwalker/Development/Gitea-Tools/mcp_server.py"],
  "env": {}
}

Restart Antigravity to load the server. Tools appear as lazy-loaded MCP tools (call via call_mcp_tool with ServerName: "gitea-tools").

Claude Code (Anthropic)

Add to ~/.claude.json (global) or .mcp.json in the project root:

{
  "mcpServers": {
    "gitea-tools": {
      "command": "/Users/jasonwalker/Development/Gitea-Tools/venv/bin/python3",
      "args": ["/Users/jasonwalker/Development/Gitea-Tools/mcp_server.py"]
    }
  }
}

Restart Claude Code. Tools appear as mcp__gitea-tools__gitea_create_issue, etc.

Any MCP-compatible client

The server is a standard MCP stdio server. Point your client at:

Command: /Users/jasonwalker/Development/Gitea-Tools/venv/bin/python3
Args: ["/Users/jasonwalker/Development/Gitea-Tools/mcp_server.py"]
Transport: stdio

No environment variables needed — auth is handled via macOS keychain.

Codex / non-MCP tools

OpenAI Codex and other tools that don't support MCP can use the CLI scripts directly. See the CLI Scripts section below.

# Example: Codex can shell out to the scripts
python3 /Users/jasonwalker/Development/Gitea-Tools/create_issue.py \
  --remote prgs --title "Bug report" --body "Details here"

CLI Scripts

The MCP tools can also be used as standalone CLI scripts:

Script	Description
`create_issue.py`	Create an issue (`--remote`, `--title`, `--body`, `--body-file`)
`create_pr.py`	Open a Pull Request (`--remote`, `--title`, `--head`, `--base`)
`close_issue.py`	Close a specific issue
`mark_issue.py`	Claim/release an issue via `status:in-progress` label
`manage_labels.py`	Create label set and apply label mappings (`--dry` to preview)
`mirror_refs.sh`	Mirror branches + tags between dadeschools ⇄ prgs

Quick Examples

# Create an issue
./create_issue.py --title "Fix PDF output" --body "Blank on Safari"

# Create an issue on the prgs instance
./create_issue.py --remote prgs --title "Add tests" --body-file description.md

# Create a PR
./create_pr.py --title "feat: add validation" --head feat/validation --body "Closes #12"

# Close issue #5
./close_issue.py 5

# Claim an issue before working on it
./mark_issue.py 10 start

# Release when done
./mark_issue.py 10 done

# Mirror refs (dry-run by default)
./mirror_refs.sh

# Actually push the refs
./mirror_refs.sh --apply

Use --help on any Python script or shell script for full usage details.

Architecture

gitea_auth.py    ← shared auth & API helpers (get_credentials, api_request)
mcp_server.py    ← MCP server (FastMCP, stdio transport)
create_issue.py  ← CLI: create issues
create_pr.py     ← CLI: create PRs
manage_labels.py ← CLI: label management
close_issue.py   ← CLI: close issues
mark_issue.py    ← CLI: claim/release issues
mirror_refs.sh   ← CLI: ref mirroring

Tests

# Run with the venv (includes MCP SDK)
source venv/bin/activate
python3 -m pytest tests/ -v

Test file	Covers
`test_mcp_server.py`	All 7 MCP tools: create, list, view, close, mark, PR, mirror
`test_create_issue.py`	CLI arg parsing, remote resolution, payload, auth, errors
`test_create_pr.py`	CLI arg parsing, remote resolution, payload, auth, errors
`test_credentials.py`	`get_credentials()`, `get_auth_header()`, `repo_api_url()`
`test_manage_labels.py`	Label create/skip, dry run, mapping, constant validation
`test_python_cli.py`	`close_issue.py` + `mark_issue.py` CLI validation
`test_mirror_refs.py`	Flags, safety defaults, local integration tests

All tests mock network and keychain access — no real API calls are made.