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Baton

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Pass the baton between coding agents: convert sessions across Claude Code, OpenCode, Codex & more.

Quick Install

Automated & IDE Setup

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

Add to CursorAdd to VS Code
Manual Client & Custom JSON ConfigExpand JSON β–Ύ

Client Config & Setup

Choose your client or environment
Target File:~/Library/Application Support/Claude/claude_desktop_config.json
claude_desktop_config.json
{
  "mcpServers": {
    "baton-2": {
      "command": "npx",
      "args": [
        "-y",
        "baton-2"
      ]
    }
  }
}

πŸ’‘ Paste the JSON block into your client's configuration file under mcpServers, then restart the application.

Install Directory Badge Claim listing AlternativesπŸ’» More in Developer Tools

Documentation Overview

baton

Pass the baton between coding agents.

Convert any coding-agent session to any other. One command. Keep going where you left off.

crates.io npm CI agents license

baton converting a Claude Code session to opencode

A passed transcript kept 14/17 concrete facts. A hand-written handoff summary kept 3/17. Benchmark ↓


The 4 p.m. problem

It's 4 p.m. Claude Code says "usage limit reached β€” resets at 10 p.m." You're three hours into a session: architecture decided, edge cases mapped, half the diff written.

❌ Without baton β€” open another agent and start from zero. Re-explain the plan. Re-read the files. Re-litigate every decision you already made.

βœ… With baton β€” pass the session and keep going:

sh
baton convert --from claude-code --to opencode --latest --import
# using latest claude-code session: 2026-07-09 15:58  Refactor the auth middleware to…
# passed baton: claude-code β†’ opencode (1388 messages) β†’ handoff.json
# Imported session: ses_8c4c973a521549e2

opencode -s ses_8c4c973a521549e2   # same conversation, different runner

Works in every direction: switch agents mid-task, try a second opinion on a hard bug, move a session from your editor agent to a terminal agent, or archive everything in one format.

Quick start

server.ts
# zero-install run (downloads prebuilt binary)
npx @kasabeh/baton-mcp --help

# convert your most recent session + auto-import into the target agent
baton convert --from claude-code --to opencode --latest --import

# or omit the path to pick interactively β€” newest first,
# each session previewed by its first user message
baton convert --from claude-code --to opencode --import

# or pass an explicit session file
baton convert --from claude-code --to opencode <session.jsonl> --import

# see every session on your machine, across all agents
baton list

Where do session files live?

You never have to hunt these down (--latest and the interactive picker find them for you), but for reference β€” each agent stores its transcripts on disk:

AgentLocation
Claude Code~/.claude/projects/<encoded-cwd>/<session-uuid>.jsonl
Codex CLI~/.codex/sessions/<YYYY>/<MM>/<DD>/rollout-*.jsonl

baton list prints the path of every session it can find, across all agents.

Supported formats

AgentReadWriteAuto-import
Claude Codeβœ…βœ…β€”
OpenCodeβœ…βœ…βœ… opencode import
Codex CLIβœ…βœ…β€”
Gemini CLIβœ…βœ…β€”
Zedβœ…βœ…β€”
Aiderβœ…βœ…β€”
Cursorβœ…ΒΉβ€”Β²β€”
Continueβœ…β€”β€”
Cline / Rooβœ…β€”Β²β€”

ΒΉ Cursor reads from exported JSON (sqlite3 state.vscdb "SELECT value FROM ItemTable WHERE key='aiService:chats'")

Β² Not planned: Cursor and Cline keep session state inside editor databases (SQLite / VS Code globalState) with no file-level import path.

Benchmark

Does carrying the full transcript beat writing a handoff summary for the next agent? We measured both on a real 3.4 MB Claude Code session (same model both arms, only the context differs):

session sizebaton transcripthandoff summary
sm (93 KB)3/3 details recalled1/3
md (198 KB)6/61/6
lg (599 KB)5/81/8
total14/173/17

The summary lost concrete facts (versions, line counts, MSRV) even on the smallest slice β€” the receiving agent had to re-read files and re-run commands to rediscover them. Mechanical fidelity: all 896 messages are written to every target; round-trip loss reflects each target format's expressiveness (claude-code 896/896, codex 736, gemini-cli 723, aider 111 β€” it stores chat text only).

We also measured task continuation: cut the session at three mid-task points, ask a fresh agent to state the task, state, and next steps. Result: parity (baton 10/12, handoff 10/12) β€” a good summary is enough for what to do next; the transcript is what answers the specific factual questions the summary's author didn't anticipate. And the summary only exists if an agent spends a full transcript read writing it β€” baton makes the transfer free.

Full methodology, caveats, and reproduction steps: benchmark/RESULTS.md.

MCP server

baton is also an MCP server β€” your agent can pass the baton itself, mid-conversation:

ToolDescription
list_sessionsScan all agents, return a unified list
convert_sessionConvert a session from one format to another
import_to_targetConvert + run the target agent's import command
detect_formatSniff a file/dir and report which agent produced it
sh
baton install     # registers baton in every detected agent's MCP config
baton doctor      # verify
baton uninstall   # remove from all agents

How it works

server.ts
Claude Code session (.jsonl)
      β”‚
      β–Ό
  baton read ──► canonical Session { messages: [Text, Reasoning, ToolCall, ToolResult] }
      β”‚
      β–Ό
  baton write ──► OpenCode import JSON (SessionV1 schema)

Every agent format is read into a canonical intermediate representation, then written out in the target format. Adding a new format is O(1), not O(NΓ—M) per-pair converters.

Install

sh
# npm (prebuilt binary, no Rust needed)
npm install -g @kasabeh/baton-mcp

# Homebrew
brew install kaseban/tap/baton-mcp

# Cargo binstall (prebuilt binary)
cargo binstall baton-mcp

# Cargo (from source)
cargo install baton-mcp

# Shell installer (prebuilt binary)
curl --proto '=https' --tlsv1.2 -LsSf https://github.com/Kaseban/baton/releases/latest/download/baton-mcp-installer.sh | sh

Or grab a binary from GitHub Releases.

Building

sh
git clone https://github.com/Kaseban/baton.git
cd baton
cargo build --release
./target/release/baton --help

Contributing

Each format lives in src/formats/<name>.rs and implements the Format trait (read + write). See src/formats/claude_code.rs for a complete reference implementation.

All nine formats have readers; Claude Code, OpenCode, Codex, Zed, Aider, and Gemini CLI also have writers. The most impactful contribution now is a writer for Continue.

Regenerating the demo

The README GIF is scripted with VHS: vhs assets/demo.tape. It records against a sandboxed $HOME (/tmp/demo) populated with fabricated sessions, so no real session data ends up in the GIF.

Don't drop the baton.

License

Dual-licensed under MIT OR Apache-2.0.

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

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Reviews

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Frequently Asked Questions about Baton

Add the following block to your claude_desktop_config.json under mcpServers: "mcpServers": { "baton": { "command": "npx", "args": ["-y", "baton"] } }

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Technical Specs & Signals

CategoryπŸ’»Developer Tools
More technical detailsExpand β–Ύ
TransportSTDIO
RuntimeNode.js
Last updatedSep 7, 2026
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27Quality signal: Emerging Β· 27/100How this signal is calculated β–Ύ
Server availabilityNot measured

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

Verified ownership8/20
Documentation & tools11/30
Adoption & activity1/15
Community engagement0/10

A guidance signal from public completeness & health data β€” 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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The official MCP server for AllMCPs.com - submit and manage tools directly from your AI. The open directory for MCP servers. Connect Claude, Cursor, Windsurf, and AI agents to databases, tools, files, and APIs. Explore 10,000+ servers. AllMCPs is the premier, open directory for discovering, evaluating, and installing Model Context Protocol (MCP) servers to equip AI agents and LLMs with real-world superpowers.

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