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fish_bridge — Quickstart

Prerequisites

  • Python 3.11+
  • An LLM API key (Gemini, Anthropic, or local Ollama)

Install

pip install fish-bridge-mcp
# or with a cloud backend extra (Gemini recommended)
pip install "fish-bridge-mcp[gemini]"
# See README for uv tool install (recommended) and other backends

1-minute setup

# Initialize for this project folder
fish-bridge init

# Configure your backend (set the API key as an environment variable)
export GEMINI_API_KEY=your-key-here
fish-bridge config --backend gemini
# or: --backend claude / --backend openai / --backend local

# Ingest the latest VS Code Copilot session (auto-discovered)
fish-bridge ingest --source copilot
# Or ingest from a saved export file:
fish-bridge ingest --source file --file path/to/export.json

# Compile context to your instructions file
fish-bridge compile --output .github/copilot-instructions.md

Ingest sources

Command What it ingests
ingest --source copilot VS Code Copilot JSONL — auto-discovered from workspaceStorage
ingest --source paste Any chat tool — opens $EDITOR, paste and save
ingest --source file --file export.json From a saved export file (Claude JSON, plain text)
merge --source document --file HANDOVER.md Markdown / text docs
merge --source codebase --path . Git log + README
merge --source obsidian --vault ~/notes Obsidian vault
merge --source deps --path . package.json / pyproject.toml etc.
merge --source testout --file results.json Jest/pytest/JUnit test output

View your graph

fish-bridge serve        # opens http://localhost:8080 (Cytoscape.js)
fish-bridge show         # pretty-print nodes in terminal

MCP server

fish-bridge serve-mcp    # starts MCP server on stdio

Add to VS Code settings.json (see examples/copilot-mcp-config.json) or Claude Desktop claude_desktop_config.json (see examples/claude-mcp-config.json).

Next steps