fish-bridge — Session Knowledge Graph

Name: fish-bridge — Session Knowledge Graph
Author: MakeaMouse

by MakeaMouseversion 0.1.3i★ –iRuns on your computer

Registry nameio.github.MakeaMouse/fish-bridge-mcp

Install

Overview

Description from the maker (original English)

Compresses AI chat sessions into a typed knowledge graph. Local/offline via Ollama.

PopNx MCP’s three pillars

These three are never merged into one score: opinions, measurements and popularity are different things.

User voiceiNo reviews yetReviews open together with accounts in a later step
Our basic checksi1 of 1 passedChecked from public information; code not scanned yet
UsageiNot measured yet★ –

What you can do with it

We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.

Connection: Runs on your computer
Transport: stdio
Category: Search & AI memory
You need to fill in: ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY

Install

Pick the AI app you use, then copy the settings.

Before you install

Basic checks: 1 of 1 passed
Runs on your computer with your user’s permissions (files, network, apps).
You fill in yourself: ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY

Values marked secret are keys to your account. Never share them or paste them into a chat.

You need

PyPIPython’s uv installed (for the uvx command)

Which app do you use?

ClaudeClaude CodeCursorVS CodeChatGPT

Pick your app above. We remember it, so next time the button says “Install in …”.

Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json

{
  "mcpServers": {
    "fish-bridge": {
      "command": "uvx",
      "args": [
        "fish-bridge-mcp"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value",
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

Run this in your terminal

claude mcp add fish-bridge --env ANTHROPIC_API_KEY=your-value --env OPENAI_API_KEY=your-value --env GEMINI_API_KEY=your-value -- uvx fish-bridge-mcp

Fill in the empty values before running it.

Open in Cursor

Or copy the settings yourself

Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json

{
  "mcpServers": {
    "fish-bridge": {
      "command": "uvx",
      "args": [
        "fish-bridge-mcp"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value",
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

Open in VS Code

Or copy the settings yourself

Paste into .vscode/mcp.json in your project

{
  "servers": {
    "fish-bridge": {
      "type": "stdio",
      "command": "uvx",
      "args": [
        "fish-bridge-mcp"
      ],
      "env": {
        "ANTHROPIC_API_KEY": "your-value",
        "OPENAI_API_KEY": "your-value",
        "GEMINI_API_KEY": "your-value"
      }
    }
  }
}

Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.

This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.

Your choice stays on this device in a cookie; no account needed.

Values you fill in

ANTHROPIC_API_KEY secret env
API key for Claude extraction backend (omit when using local/Ollama)
OPENAI_API_KEY secret env
API key for OpenAI extraction backend (omit when using local/Ollama)
GEMINI_API_KEY secret env
API key for Gemini extraction backend (omit when using local/Ollama)

These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.

What it can do

Runs on your computer; the tool list appears in your AI app after you install it.

Basic checksi

We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026

✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account MakeaMouse, which owns the repo
… Not checked yet
Still maintained
We have not read this repo from GitHub yet
… Not checked yet
Has a licence
We have not read this repo from GitHub yet
– Not applicable
Endpoint responds
This one runs on your computer; there is no internet endpoint
– Not applicable
Sign-in with OAuth
Runs on your computer and uses local settings instead
… Not checked yet
No hidden instructions in tool descriptions
Runs on your computer; we can only read tool lists from internet endpoints

Compared with others in Search & AI memoryi

More stars than 0% of the other 7258 servers in this category
Published to the registry more recently than 13% of the other 7258 servers in this category
Basic checks equal to or better than 100% of the other 7258 servers in this category

Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.

Common questions

Is fish-bridge — Session Knowledge Graph safe?

It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.

What keys or codes does it need?

You need to fill in: ANTHROPIC_API_KEY, OPENAI_API_KEY, GEMINI_API_KEY

Does it run on my computer or in the cloud?

It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).

Is it still maintained?

The GitHub repo last changed –, and the latest version (0.1.3) reached the registry 6 months ago.

Which apps can use it?

Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.

What can I use instead?

In the same category: Context7, Codebase Memory, Exa

Alternatives

Servers in the same category from other makers, sorted by stars.

Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi

Context7

by upstash

Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.

Computer or cloud★ 64,224MITUpdated today

Install

Codebase Memory

by DeusData

Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.

Runs on your computer★ 48,148MITUpdated 20 days ago

Install

Exa

by exa-labs

Connect AI agents to Exa for web search, content fetching, and multi-step research.

Runs in the cloud★ 5,213MITUpdated last month

Install

README from the maker

Open the README

Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.

fish_bridge

Session-scoped knowledge graph engine for AI chat context compression.

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-bridge` — the main CLI (ingest, compile, show, serve, ...)
`fish-bridge-mcp` — the MCP server for VS Code agent mode

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"] }

See the MCP server section below for the full config.

Traditional pip install (for embedding fish-bridge as a library in your own Python project)

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

</details>

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

Backend	Install extra	Model	Quality	Cost/turn
`local` (Ollama)	(none — requires Ollama)	qwen2.5:7b	~85%	$0
`gemini`	`[gemini]`	gemini-2.5-flash	~95%	~$0.0002
`openai`	`[openai]`	gpt-4.1-mini	~93%	~$0.0003
`claude`	`[claude]`	claude-opus-4-7	~97%	~$0.002
`hybrid`	`[claude]` or `[openai]`	local+cloud	best	mixed

Configure with:

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 # 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 --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

Source	Command	What it ingests
Copilot	`ingest --source copilot`	VS Code Copilot JSONL transcript (auto-discovered)
Paste	`ingest --source paste`	Any chat text — universal fallback
Document	`merge --source document`	Markdown, JSON, YAML specs and ADRs
Codebase	`merge --source codebase`	Git commits + README + HANDOVER
Obsidian	`merge --source obsidian`	Vault notes with wikilinks and frontmatter
Session	`merge --source session`	Prior `.chatgraph.json` export
Deps	`merge --source deps`	package.json, pyproject.toml, Cargo.toml, go.mod, Gemfile, pom.xml
Test output	`merge --source testout`	Jest JSON, pytest JSON, JUnit XML — error nodes per failing test
IaC	`merge --source iac`	Terraform, CDK (synth output), CloudFormation, docker-compose
OpenAPI	`merge --source openapi`	OpenAPI 3.x / Swagger 2.0 / AsyncAPI specs

How it works

Ingest — reads raw chat turns from JSONL (Copilot), paste, or any file format
Extract — LLM extracts typed nodes (questions, decisions, errors, tasks, skills, files) and edges
Dedup — semantic similarity merges near-duplicates; conflict detection flags status reversals
Compile — graph is compressed to ~300–800 token XML/markdown block
Write — 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

Quickstart
Configuration
Graph schema
Compiler modes
Ingestors

License

MIT — see LICENSE

fish-bridge — Session Knowledge Graph

Overview

PopNx MCP’s three pillars

What you can do with it

Install

Before you install

Values you fill in

What it can do

Basic checksi

Maker matches the repo

Still maintained

Has a licence

Endpoint responds

Sign-in with OAuth

No hidden instructions in tool descriptions

Compared with others in Search & AI memoryi

Common questions

Alternatives

Context7

Codebase Memory

Exa

README from the maker

fish_bridge

Install

Gemini backend (~$0.0002/turn, ~95% quality — recommended cloud option)

Claude backend (~$0.002/turn, ~97% quality)

OpenAI backend (~$0.0003/turn, ~93% quality)

Everything

2-minute quickstart

2. Ingest the latest Copilot session (auto-discovers JSONL on macOS/Linux/Windows)

3. View the graph

4. Compile to your instructions file (done automatically after ingest)

Backends

or set GEMINI_API_KEY / ANTHROPIC_API_KEY / OPENAI_API_KEY as env vars

Full CLI reference

--- Ingest chat turns ---

--- Merge external knowledge ---

--- Compile & view ---

--- Node management ---

--- Export / import / diff ---

--- Config ---

MCP server (optional — agent mode only)

Ingest sources

How it works

Documentation

License