baton-mcp
This server does not currently have a deployable release on Glama. Follow the repository's setup instructions to install and configure it for your MCP client, including any required credentials and local dependencies.
Pass the baton between coding agents.
Convert any coding-agent session to any other. One command. Keep going where you left off.
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 — resets at 10 p.m." You're three hours into a session: architecture decided, edge cases mapped, half the diff written.
❌ Without baton — open another agent and start from zero. Re-explain the plan. Re-read the files. Re-litigate every decision you already made.
✅ With baton — pass the session and keep going:
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 → opencode (1388 messages) → handoff.json
# Imported session: ses_8c4c973a521549e2
opencode -s ses_8c4c973a521549e2 # same conversation, different runnerWorks 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.
Related MCP server: chat-across
Quick start
# 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 — 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 listWhere do session files live?
You never have to hunt these down (--latest and the interactive picker find them for you), but for reference — each agent stores its transcripts on disk:
Agent | Location |
Claude Code |
|
Codex CLI |
|
baton list prints the path of every session it can find, across all agents.
Supported formats
Agent | Read | Write | Auto-import |
Claude Code | ✅ | ✅ | — |
OpenCode | ✅ | ✅ | ✅ |
Codex CLI | ✅ | ✅ | — |
Gemini CLI | ✅ | ✅ | — |
Zed | ✅ | ✅ | — |
Aider | ✅ | ✅ | — |
Cursor | ✅¹ | —² | — |
Continue | ✅ | — | — |
Cline / Roo | ✅ | —² | — |
¹ Cursor reads from exported JSON (sqlite3 state.vscdb "SELECT value FROM ItemTable WHERE key='aiService:chats'")
² 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 size | baton transcript | handoff summary |
sm (93 KB) | 3/3 details recalled | 1/3 |
md (198 KB) | 6/6 | 1/6 |
lg (599 KB) | 5/8 | 1/8 |
total | 14/17 | 3/17 |
The summary lost concrete facts (versions, line counts, MSRV) even on the smallest slice — 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 — 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) — 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 — baton makes the transfer free.
Full methodology, caveats, and reproduction steps: benchmark/RESULTS.md.
MCP server
baton is also an MCP server — your agent can pass the baton itself, mid-conversation:
Tool | Description |
| Scan all agents, return a unified list |
| Convert a session from one format to another |
| Convert + run the target agent's import command |
| Sniff a file/dir and report which agent produced it |
baton install # registers baton in every detected agent's MCP config
baton doctor # verify
baton uninstall # remove from all agentsHow it works
Claude Code session (.jsonl)
│
▼
baton read ──► canonical Session { messages: [Text, Reasoning, ToolCall, ToolResult] }
│
▼
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(N×M) per-pair converters.
Install
# 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 | shOr grab a binary from GitHub Releases.
Building
git clone https://github.com/Kaseban/baton.git
cd baton
cargo build --release
./target/release/baton --helpContributing
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.
This server cannot be deployed
Maintenance
Related MCP Connectors
Hand off the context of an AI conversation to another AI tool, or to someone else's AI.
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One shared project for a team's coding agents: decisions, a task board and handoffs.
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