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  1. Home
  2. ๐Ÿง  Knowledge & Memory
  3. Fish Bridge MCP
Fish Bridge MCP logo
Health: ActiveRecent health check succeeded.Last checked 9/9/2026, 5:49:30 PM

Fish Bridge MCP

User RatingsBe the first to rate and review this MCP server!
View Repository2 GitHub StarsTotal stargazers on GitHub for the source repository (2 stars).Visit Website
knowledge-graphcontext-compressiondeveloper-toolslocal-ai

Compresses AI chat sessions into typed knowledge graphs and writes compact context files for future coding-agent turns.

Quick Install

Automated & IDE Setup

Copy the AI prompt to install this server into Claude Code, Cursor, or another agent โ€” or use 1-click editor setup below.

Add to CursorAdd to VS Code
Not yet automatically verified

We haven't yet run this listing's install command through our automated sandbox check. This isn't a red flag โ€” we're steadily working through the catalog.

Manual Client & Custom JSON ConfigExpand JSON โ–พ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "makeamouse-fish-bridge-mcp": {
      "command": "uvx",
      "args": [
        "fish-bridge-mcp"
      ]
    }
  }
}

๐Ÿ’ก Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing Alternatives๐Ÿง  More in Knowledge & Memory

Overview

fish-bridge converts long AI chat sessions into compact typed knowledge graphs of about 300โ€“800 tokens. It can write these graphs to .github/copilot-instructions.md or CLAUDE.md for automatic inclusion in later turns. Use it for session context compression, project handovers, and merging external project knowledge; its core workflow does not require an MCP server.

Use cases

โ€ขCompress long Copilot or coding-agent sessions into reusable context
โ€ขWrite session summaries to project instruction files
โ€ขMerge codebases, documents, dependencies, tests, and infrastructure into a knowledge graph
โ€ขGenerate focused context or handover digests
โ€ขRun local extraction with Ollama without a paid API

Key features

โ€ขTyped knowledge graph generation
โ€ขCopilot and Claude instruction-file output
โ€ขSession ingestion from Copilot, pasted text, or files
โ€ขExternal knowledge merging
โ€ขGraph viewing and node resolution or deferral
โ€ขLocal Ollama and cloud model backends

Capabilities & Tool Schemas

Inspect callable tools, capabilities, and parameters exposed to AI agents by Fish Bridge MCP.

Extracted Tool Capabilities
Typed knowledge graph generation
Copilot and Claude instruction-file output
Session ingestion from Copilot, pasted text, or files
External knowledge merging
Graph viewing and node resolution or deferral
Local Ollama and cloud model backends

Documentation Overview

fish_bridge

CI PyPI Python License: MIT

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

Converts raw AI chat (40k+ tokens) into a compact typed knowledge graph (~300โ€“800 tokens) and writes it to .github/copilot-instructions.md or CLAUDE.md โ€” automatically included in every AI turn across all modes (ask, edit, agent). No MCP server required for the core workflow.

Code
Raw session (40k tokens) โ†’ [fish_bridge] โ†’ 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 โ€” no virtualenv management needed.

Recommended โ€” uv tool install (installs both the fish-bridge CLI and fish-bridge-mcp MCP server on your PATH):

server.ts
# Local Ollama backend โ€” free, offline (requires Ollama running)
uv tool install fish-bridge-mcp

# Gemini backend (~$0.0002/turn, ~95% quality โ€” 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 โ€” the main CLI (ingest, compile, show, serve, ...)
  • fish-bridge-mcp โ€” the MCP server for VS Code agent mode

MCP config only (no permanent install needed): use uvx directly in your .vscode/mcp.json โ€” it downloads and runs the MCP server on demand:

config.json
{ "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)
Terminal
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

bash
# 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

BackendInstall extraModelQualityCost/turn
local (Ollama)(none โ€” 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+cloudbestmixed

Configure with:

bash
fish-bridge config --backend gemini
# or set GEMINI_API_KEY / ANTHROPIC_API_KEY / OPENAI_API_KEY as env vars

Full CLI reference

server.ts
# --- Session init ---
fish-bridge init                          # create session for current project
fish-bridge init --tool claude            # โ†’ 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 โ€” 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 โ€” agent mode only)

The MCP server adds real-time record_turn capture when using VS Code agent mode. It is not required โ€” the file-based workflow above works in all modes without it.

Add to .vscode/mcp.json (uses uvx โ€” no prior install needed):

config.json
{
  "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:

config.json
{ "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

SourceCommandWhat it ingests
Copilotingest --source copilotVS Code Copilot JSONL transcript (auto-discovered)
Pasteingest --source pasteAny chat text โ€” universal fallback
Documentmerge --source documentMarkdown, JSON, YAML specs and ADRs
Codebasemerge --source codebaseGit commits + README + HANDOVER
Obsidianmerge --source obsidianVault notes with wikilinks and frontmatter
Sessionmerge --source sessionPrior .chatgraph.json export
Depsmerge --source depspackage.json, pyproject.toml, Cargo.toml, go.mod, Gemfile, pom.xml
Test outputmerge --source testoutJest JSON, pytest JSON, JUnit XML โ€” error nodes per failing test
IaCmerge --source iacTerraform, CDK (synth output), CloudFormation, docker-compose
OpenAPImerge --source openapiOpenAPI 3.x / Swagger 2.0 / AsyncAPI specs

How it works

  1. Ingest โ€” reads raw chat turns from JSONL (Copilot), paste, or any file format
  2. Extract โ€” LLM extracts typed nodes (questions, decisions, errors, tasks, skills, files) and edges
  3. Dedup โ€” semantic similarity merges near-duplicates; conflict detection flags status reversals
  4. Compile โ€” graph is compressed to ~300โ€“800 token XML/markdown block
  5. Write โ€” block is written to .github/copilot-instructions.md (or CLAUDE.md)
  6. Deliver โ€” AI tool reads the file automatically on the next turn โ€” no injection, no agent required

Documentation

  • Quickstart
  • Configuration
  • Graph schema
  • Compiler modes
  • Ingestors

License

MIT โ€” see LICENSE

Read the full README โ†’View source on GitHub โ†’

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Adoption & maintenance

Factual signals from GitHub, npm, and our automated checks โ€” not a rating.

GitHub stars
2
Stargazers on the source repository.
Last commit
1mo ago
Most recent push to the default branch.
Directory activity
1 views
Config copies, upvotes, and views on AllMCPs.

Reviews

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Frequently Asked Questions about Fish Bridge MCP

No. The core file-based workflow does not require MCP server mode; an optional MCP server is available for VS Code agent mode.

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Technical Specs & Signals

Category๐Ÿง Knowledge & Memory
PricingFree
More technical detailsExpand โ–พ
TransportSTDIO
RuntimePython
AuthNo auth required
LicenseMIT
ClientsCursor
Last updatedAug 11, 2026
Views1
Unique ViewsTotal visits recorded for this listing page on AllMCPs.
Installs0
Installs & Copy ActionsTotal times users copied install commands or configuration snippets for this server.
GitHub stars2
GitHub Star CountTotal stargazers on GitHub representing community popularity (2 stars).
Last commit1mo ago
Last Repository CommitThe most recent commit or push recorded for this server's GitHub repository.Last commit on Jul 30, 2026
49Quality signal: Fair ยท 49/100How this signal is calculated โ–พ
Server availabilityNot measured

Not scored for repo-hosted servers โ€” we can't reach the running server, only its GitHub page. Hosted MCP endpoints are health-checked live.

Verified ownership10/20
Documentation & tools24/30
Adoption & activity3/15
Community engagement0/10

A guidance signal from public completeness & health data โ€” not a user rating. New listings start lower and rise as they add docs, get verified, and grow adoption. Signals we can't observe for a listing are skipped, not counted against it.

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Scanned 27d ago via OSV.dev ยท fish-bridge-mcp (PyPI)

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