MCP-сервер Fish Bridge — Session Knowledge Graph | PlugMCP
К содержанию fish_bridge
Session-scoped knowledge graph engine for AI chat context compression.
Compresses AI chat sessions into a typed knowledge graph. Local/offline via Ollama.
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Продукт
Каталог
Разработчикам
Компания
ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY 2026-11-09
Звёзды —
Инструменты —
Аптайм — Converts raw AI chat (40k+ tokens) into a compact typed knowledge graph (~300–800 tokens) and writes it to .github/copilot-instructions.md or CLAUDE.md — automatically included in every AI turn across all modes (ask, edit, agent). No MCP server required for the core workflow.
Raw session (40k tokens) → [fish_bridge] → Compressed graph (350 tokens)
written to copilot-instructions.md
picked up by every AI turn automatically
Install
Don't have uv? Get it first: curl -LsSf https://astral.sh/uv/install.sh | sh (macOS/Linux) or see uv docs . It replaces pip + pipx + pyenv in one tool — no virtualenv management needed.
Recommended — uv tool install (installs both the fish-bridge CLI and fish-bridge-mcp MCP server on your PATH):
# Local Ollama backend — free, offline (requires Ollama running)
uv tool install fish-bridge-mcp
# Gemini backend (~$0.0002/turn, ~95% quality — recommended cloud option)
uv tool install "fish-bridge-mcp[gemini]"
export GEMINI_API_KEY=...
# Claude backend (~$0.002/turn, ~97% quality)
uv tool install "fish-bridge-mcp[claude]"
export ANTHROPIC_API_KEY=sk-ant-...
# OpenAI backend (~$0.0003/turn, ~93% quality)
uv tool install "fish-bridge-mcp[openai]"
export OPENAI_API_KEY=sk-...
# Everything
uv tool install "fish-bridge-mcp[all]"
After install, two commands are available on your PATH:
fish-bridgeingest, compile, show, serve, ...)fish-bridge-mcp MCP config only (no permanent install needed): use uvx directly in your .vscode/mcp.json — it downloads and runs the MCP server on demand:
{ "command": "uvx", "args": ["fish-bridge-mcp"] }
pip install fish-bridge-mcp
pip install "fish-bridge-mcp[gemini]" # with Gemini backend
pip install "fish-bridge-mcp[claude]" # with Claude backend
pip install "fish-bridge-mcp[all]" # everything
2-minute quickstart # 1. Initialize for your project
fish-bridge init --tool copilot --project ./
# 2. Ingest the latest Copilot session (auto-discovers JSONL on macOS/Linux/Windows)
fish-bridge ingest --source copilot
# 3. View the graph
fish-bridge show
# 4. Compile to your instructions file (done automatically after ingest)
fish-bridge compile
That's it. .github/copilot-instructions.md now contains a ~350-token compressed summary of your session, replacing raw history in every future turn.
Backends fish-bridge config --backend gemini
# or set GEMINI_API_KEY / ANTHROPIC_API_KEY / OPENAI_API_KEY as env vars
Full CLI reference # --- Session init ---
fish-bridge init # create session for current project
fish-bridge init --tool claude # → writes to CLAUDE.md instead
# --- Ingest chat turns ---
fish-bridge ingest --source copilot # auto-discover latest VS Code Copilot session
fish-bridge ingest --source copilot --session <id> # target specific session
fish-bridge ingest --source paste # paste any chat text — opens $EDITOR (universal fallback)
fish-bridge ingest --source file --file export.json # from a saved export file
fish-bridge watch --source copilot # tail JSONL, auto-update on new turns
# --- Merge external knowledge ---
fish-bridge merge --source document --file HANDOVER.md
fish-bridge merge --source codebase --path ./ # git log + README
fish-bridge merge --source obsidian --vault ~/notes
fish-bridge merge --source deps --path ./ # package.json / pyproject.toml etc.
fish-bridge merge --source testout --file results.json # jest / pytest / JUnit
fish-bridge merge --source iac --path ./ # Terraform / CDK / CloudFormation
fish-bridge merge --source openapi --file openapi.yaml
fish-bridge merge --source session --file prior.chatgraph.json
# --- Compile & view ---
fish-bridge compile # update instruction file (runs after ingest by default)
fish-bridge compile --mode digest # full handover markdown
fish-bridge compile --mode focus --query "Redis caching"
fish-bridge show # pretty-print active nodes
fish-bridge show --all # include resolved/deferred items
fish-bridge serve # open Cytoscape.js graph viewer at localhost:8080
fish-bridge digest # generate handover digest
# --- Node management ---
fish-bridge resolve "DNC caching strategy"
fish-bridge defer "v16 index validation"
fish-bridge add "Use Redis for session cache" --type decision
fish-bridge conflict show
fish-bridge conflict resolve <node-id> --keep old
# --- Export / import / diff ---
fish-bridge export # save .chatgraph.json
fish-bridge import prior-session.chatgraph.json
fish-bridge diff session-a.chatgraph.json session-b.chatgraph.json
# --- Config ---
fish-bridge config --show
fish-bridge config --backend gemini
MCP server (optional — agent mode only) The MCP server adds real-time record_turn capture when using VS Code agent mode. It is not required — the file-based workflow above works in all modes without it.
Add to .vscode/mcp.json (uses uvx — no prior install needed):
{
"servers": {
"fish-bridge": {
"command": "uvx",
"args": ["fish-bridge-mcp"],
"env": { "FISH_BRIDGE_BACKEND": "gemini", "GEMINI_API_KEY": "${env:GEMINI_API_KEY}" }
}
}
}
If you used uv tool install fish-bridge-mcp, you can also reference the installed binary directly:
{ "command": "fish-bridge-mcp" }
See examples/ for Claude Desktop, Cursor, and Windsurf configs.
MCP tools : record_turn, get_context, get_focus, mark_resolved, add_node, export_session, import_session, show_active, list_deferred
Ingest sources
How it works
Ingest — reads raw chat turns from JSONL (Copilot), paste, or any file formatExtract — LLM extracts typed nodes (questions, decisions, errors, tasks, skills, files) and edgesDedup — semantic similarity merges near-duplicates; conflict detection flags status reversalsCompile — graph is compressed to ~300–800 token XML/markdown blockWrite — block is written to .github/copilot-instructions.md (or CLAUDE.md)Deliver — AI tool reads the file automatically on the next turn — no injection, no agent required
Documentation
License
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Graphify Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, e Understand Anything Graphs that teach > graphs that impress. Turn any code into an interactive knowledge graph you can explore, search, and ask questions about. Works with Claude Code, Codex, Cursor, Copilot, Gemini CLI, Sequential Thinking Step-by-step problem solving for agents: break a problem into thoughts, revise them and branch. The reference server from the Model Context Protocol project. Memory Persistent memory for agents as a local knowledge graph of entities, relations and observations. The reference server from the Model Context Protocol project. Ruflo 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory, self-learning intelligence, feder Codegraph Pre-indexed code knowledge graph, auto syncs on code changes, for Claude Code, Codex, Gemini, Cursor, OpenCode, AntiGravity, Kiro, CoPilot, and Hermes Agent — fewer tokens, fewer tool calls, 100% loca Codebase Memory Local code intelligence for developers and AI agents. Connect code, docs and infrastructure in a persistent graph, with CBM Lens, MCP tools, agent integrations and change-aware test selection. Codebase Memory Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens. Codebase Memory Local code intelligence for developers and AI agents. Connect code, docs and infrastructure in a persistent graph, with CBM Lens, MCP tools, agent integrations and change-aware test selection. Context Mode Free, local plugin that keeps tool output out of your coding agent's context window. Sandbox and SQLite FTS5 search, 99% fewer bytes in context. Works with Claude Code, Codex, Pi, OMP, OpenCode, Gemin MaxKB 🔥 MaxKB is an open-source platform for building enterprise-grade agents. 强大易用的开源企业级智能体平台。 Xerj AI search engine and MCP server for bots and agents. One Rust binary indexes code, docs, logs, JSONL/CSV and PDFs for BM25 full-text, vector and hybrid search, code search without grep, agent memory a MCP-серверы: Knowledge and memory Лучшие MCP-серверы: Knowledge and memory
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Как установить Fish Bridge — Session Knowledge Graph? Скопируйте на этой странице конфигурацию stdio для Cursor, Claude Desktop, Claude Code или VS Code. Она использует установку издателя, а не прокси PlugMCP.
Нужен ли API-ключ для Fish Bridge — Session Knowledge Graph? Издатель указывает следующие переменные окружения: ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY.
Какой транспорт использует Fish Bridge — Session Knowledge Graph? Fish Bridge — Session Knowledge Graph работает локально через stdio.
Когда Fish Bridge — Session Knowledge Graph проверялся в последний раз? Последняя проверка: 2026-11-09. Compresses AI chat sessions into a typed knowledge graph. Local/offline via Ollama.
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