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Rutherford MCP Server

Rutherford MCP Server

by chapmanjw
uv tool install rutherford-mcp-server

Using Claude Code? The Rutherford Claude Plugin wraps this server with one-step setup: it auto-registers the server (no manual mcp add) and adds skills, an orchestrator agent, and slash commands for setup, panels, consensus, debate, and review. Install it with /plugin marketplace add chapmanjw/rutherford-claude-plugin then /plugin install rutherford@rutherford-claude. Either path is fully supported — reach for the plugin for a batteries-included Claude Code experience, or wire up this server directly for any MCP client.

What Rutherford is

Rutherford is a Model Context Protocol server that speaks the Agent Client Protocol on the other side. Your MCP client (a coding CLI or a desktop app) calls Rutherford's tools; Rutherford spawns each target coding agent as an ACP server over stdio and drives it through a real initialize / new_session / prompt exchange.

It is the ACP client, and each coding agent is an ACP agent. That distinction matters: under ACP the protocol negotiates the answer, token usage, tool activity, and permissions as structured events, so Rutherford never scrapes an agent's stdout and never reimplements a CLI's features. It also never calls a model provider's API directly — every answer comes from an agent you already log into, in the agent's own account.

   your MCP client (Claude Code, Cursor, Codex, Claude Desktop, ...)
        |  MCP over stdio
        v
   rutherford-mcp-server          (the ACP client)
        |  ACP over stdio, one session per voice
        +--> goose acp
        +--> codex-acp                 (the Zed adapter fronting Codex)
        +--> claude-agent-acp          (the Zed adapter fronting Claude Code)
        +--> ... 17 more built-in agents, all config-driven

A voice that fails to spawn, handshake, or answer comes back as one failed result in a structured envelope, never an aborted panel.

Related MCP server: all-agents-mcp

See it work

The mode that is not just parallel answers is debate. Round one is each voice's independent take; in every later round, each voice sees the others' latest positions and is asked to rebut and revise. Each voice keeps one persistent ACP session across the rounds, so it remembers its own prior reasoning and only the delta is sent each round — the capability the old subprocess-per-call model could not offer.

prompt   "Is UUIDv7 or ULID the better primary key for a high-write event table?"
panel    claude_code, codex, kiro    rounds: 3

round 1  claude_code   UUIDv7 — the timestamp prefix gives B-tree index locality
         codex         UUIDv7 — standardized and DB-native; monotonic within a process
         kiro          UUIDv7 — but argues ULID is BOTH lexicographically sortable AND
                       collision-resistant across concurrent writers

round 2  claude_code   flags that Kiro conflates two properties: ULID's sortability and
                       its per-process monotonicity are not the same guarantee
         codex         agrees — the monotonic guarantee is per-process, not cross-node
         kiro          revises: cross-node, UUIDv7's timestamp prefix gives the locality
                       without relying on a per-process assumption

result   converged on UUIDv7, with a closing synthesis of where the panel agreed and why

The call returns the full per-round transcript plus the closing synthesis, so you can retrace who said what and where someone revised. Debates do not always converge or change a mind, but when they do the transcript shows precisely where.

Quickstart

You bring the crew. Rutherford does not install or authenticate any coding agent — it drives the ones you already have. You need Python 3.11+ and at least two ACP-capable agents installed and signed in (two is enough for a consensus or a debate). If you already use Claude Code or Codex, you have most of what you need.

1. Install Rutherford.

uv tool install rutherford-mcp-server
# or: pipx install rutherford-mcp-server  /  pip install rutherford-mcp-server

This puts the console entry points rutherford-mcp-server and rutherford on your PATH (same process; the short name is for terminal subcommands). The same command starts the stdio server on Windows, macOS, and Linux; python -m rutherford is equivalent.

2. Register it with your MCP client.

claude mcp add rutherford -- rutherford-mcp-server      # Claude Code
codex mcp add rutherford -- rutherford-mcp-server       # Codex

For Claude Desktop, Cursor, and other JSON-config clients:

{ "mcpServers": { "rutherford": { "command": "rutherford-mcp-server" } } }

If rutherford-mcp-server is not on the client's PATH, use an absolute path, or python -m rutherford with the interpreter from the environment where you installed it. More clients and WSL: docs/mcp-client-integration.md.

3. Scaffold a config (optional). Rutherford works with zero config. To write a starter file, either run the one-shot CLI from your terminal:

rutherford-mcp-server init          # or: python -m rutherford init  [--global] [--yes]

or, once it is registered with a client, ask for the setup tool:

Run Rutherford's setup and write a project config.

Both resolve the config path, write a commented starter config.toml at the effective defaults, and never clobber an existing file. init targets <cwd>/.rutherford/config.toml (or the global path with --global); setup returns the path and content to the client and writes with write=true.

To allow write / yolo delegations into the current repo without a per-call trust_workspace=true, register cwd in the global allowlist:

rutherford-mcp-server trust           # adds cwd to global trusted_workspaces
rutherford-mcp-server trust --list    # or: python -m rutherford trust --list
rutherford-mcp-server untrust         # removes cwd from the global allowlist

Config is read once at server start, so restart or reconnect the server for a new entry to take effect.

4. Run doctor first. Multi-agent auth and PATH is the most common thing that goes wrong, so confirm the crew actually drives before your first real task:

Run Rutherford's doctor and tell me which agents spawn, handshake, and answer.

doctor probes each agent with a real read-only ACP round trip — the only trustworthy health signal, since there is no cheap non-interactive auth check. Each report is ok, no_answer, model_unavailable, handshake_failed, auth_required, not_installed, or error. An auth_required agent is installed but not yet signed in; sign it in once with login. Two or more ok agents means you are ready.

No paid agent subscription? Run your first consensus for free against a local model. With Ollama or LM Studio running, Rutherford auto-detects each tool-capable model and registers it as a goose-based agent — no key, no account. See docs/local-models.md.

The tools

You rarely call these by name; your agent picks them from your request. Everything defaults to read-only.

Tool

What it does

delegate

Hand one task to one ACP agent; get one normalized result back.

consensus

Ask the same prompt of several agents in parallel; return every voice.

debate

Have several agents argue across rounds (persistent sessions) and return the full transcript.

review

Review a diff or a working dir's changes across one or more agents — a code-review-shaped consensus.

plan

Produce an implementation plan for a task without making changes (read-only by construction).

continue_job

Resume or build on a completed durable job (delegate / consensus / debate) with a new prompt.

analyze

Run an offline report over the kept run corpus (e.g. historical_agreement cross-lineage agreement).

capabilities

List the registered agents (id, display name, launch command, provider) — the cheap snapshot.

doctor

Probe each agent with a real read-only ACP round trip and report conformance.

login

Sign an agent in once through ACP authenticate, for one doctor reports as auth_required; returns a job to poll, plus the sign-in link when the agent prints one.

discover

Detect installed ACP agents from the community registry and propose reviewable config blocks.

list_roles

List the role personas you can pass as role="<id>".

setup

Show where config lives, scaffold a starter config.toml, and install missing npm ACP adapter shims; the first-run helper.

reload_panels

Reload the named multi-agent panel definitions from config without restarting the server.

list_jobs

List the background jobs being tracked (every status), newest first.

activity

Show only the jobs in flight right now, each with a live elapsed time.

job_status

Report one background job's status and timings.

job_result

Return a finished job's result envelope (identical to the sync envelope).

cancel_job

Cancel a running background job and tear down its work.

Shared arguments on delegate / consensus / debate: working_dir, files (paths to put in scope), safety_mode, timeout_s, role, and mode (sync or async). delegate also takes trust_workspace for the mutating modes; debate takes rounds, judge, and synthesize.

The agent roster

Rutherford ships 21 built-in agents with curated launch commands and quirks (the Windows npm-shim resolution, per-agent handshake budgets, a fixed provider) that a bare acp.json cannot express, so they work with zero config:

id

agent

how it launches

login

goose

Goose

goose acp

provider key / goose configure

opencode

OpenCode

opencode acp

a configured provider

vibe

Mistral Vibe

vibe-acp

Mistral / vibe login

cline

Cline

cline --acp

Cline's own service auth

junie

Junie

junie --acp=true

JetBrains login

kimi

Kimi Code

kimi acp

Moonshot login

openhands

OpenHands

openhands acp

a configured provider

codex

Codex

codex-acp

the existing Codex (ChatGPT) login — no API key

claude_code

Claude Code

claude-agent-acp

the existing Claude Code login — no API key

copilot

GitHub Copilot

copilot --acp

GitHub Copilot plan

qwen

Qwen Code

qwen --acp

Qwen OAuth / OpenAI-compatible key

droid

Factory Droid

droid exec --output-format acp

Factory login

cursor

Cursor

cursor-agent acp

Cursor subscription

kiro

Kiro

kiro-cli acp

Kiro login / KIRO_API_KEY

pi

Pi

pi-acp

Pi login

hermes

Hermes

hermes acp

Nous endpoint

gemini

Gemini CLI

gemini --acp

Google / Gemini CLI login

qoder

Qoder

qodercli --acp

Qoder login

grok

Grok

grok agent stdio

xAI login + SuperGrok subscription

fast_agent

fast-agent

uvx fast-agent-acp==0.8.3

provider API key (env or fast-agent.secrets.yaml)

antigravity

Google Antigravity

agy_acp_server (macOS: agy_acp_server.par; Linux: agy_acp_server.par --uid=)

Google sign-in, once, with the login tool

codex and claude_code launch through the official Zed adapters (codex-acp and claude-agent-acp, npm @agentclientprotocol/*), which front the Codex and Claude Code CLIs as ACP servers and reuse the existing CLI login — no API key. cline drives over ACP only with Cline's own service auth (a ChatGPT-subscription or OpenRouter provider set in the desktop app does not reach the headless --acp path). hermes depends on the configured Nous model and its latency can be high. gemini is Google's official Gemini CLI (the --acp mode works as of CLI 0.46.0). qoder's --acp flag is real but hidden from --help, and Qoder's installer drops qodercli at ~/.qoder/bin/ rather than on PATH — add that directory to PATH, point [agents.qoder] command at the full path, or let discover find it. grok (xAI) is ACP-native and connects cleanly, but a completed turn needs a SuperGrok subscription — without it the model call returns 403; run doctor connect_only=true to confirm Rutherford can reach and configure it (it reports reachable and the advertised models) independent of the entitlement. antigravity is Google Antigravity's ACP server, which Google now points individual Gemini accounts to (Gemini CLI refuses them). It is a standalone binary from the ACP registry, separate from the agy CLI, and is not installed onto PATH, so add its directory to PATH or set [agents.antigravity] command to the full path. Until it has been signed in once, doctor reports it as auth_required: run login agent=antigravity method=oauth-personal, open the returned sign-in link (Antigravity prints one; if signin_urls is empty the agent may have opened a browser itself), and poll job_status / job_result with the returned job_id. The server caches the credential under ~/.gemini/antigravity-acp/ ($GEMINI_HOME relocates it), so later sessions open without it. It has been verified on Windows; the macOS and Linux launch commands (including the --uid= argument Linux gets) come from the registry entry and are not yet verified. If it fails to launch on Linux, try [agents.antigravity] command = ["agy_acp_server.par"] to drop that argument.

Not every agent drives cleanly on every machine — run doctor to see which actually answer here.

Config-driven agents. Under ACP an agent is just how to launch it plus a few quirks, so the roster is config-driven. An [agents.<id>] section overrides a built-in's command / env / provider / model, disables one with enabled = false, or defines a brand-new agent (any unknown id, which must supply a launch command). enabled_agents restricts the registry to an allowlist. The launch fields mirror the Zed/Cline acp.json shape, and the loader auto-imports an acp.json beside the global config or in the project's .rutherford/. See docs/adding-an-agent.md.

Local models. With auto_detect_local_models on (the default), Rutherford probes a running Ollama (:11434) and LM Studio (:1234) at startup and registers each tool-capable model as a goose-based ACP agent automatically. You can also point an agent at a local runtime by hand. See docs/local-models.md.

Safety modes

Every delegation runs in one of four modes, defaulting to the most restrictive. Rutherford is the permission authority at the moment of each ACP tool call: it answers the agent's filesystem-write, terminal-execution, and tool-permission requests according to the mode.

Mode

Meaning

read_only (default)

Inspect only. Reads are served; writes, terminal execution, and tool-permission requests are denied.

propose

Same denials as read_only — the agent may describe changes but not apply them.

write

The agent may modify the workspace, subject to the agent's own approvals.

yolo

The agent may act without approval prompts.

A call that omits safety_mode adopts the configured default_safety_mode (read_only out of the box); an explicit value always wins. write and yolo require a trusted workspace: the target working_dir must be on the trusted_workspaces allowlist, or the call must pass trust_workspace=true. Full detail: docs/security.md.

Jobs, roles, and config

Background jobs. Pass mode="async" to delegate / consensus / debate to run the work off the request path: the call returns a small {job_id, status, tool} envelope immediately, and the work runs as an in-memory task. Manage it with list_jobs, activity, job_status, job_result, and cancel_job. A finished job's result envelope is byte-for-byte the same as the sync path's. Jobs are in-memory and clear on restart.

Roles. A role is a reusable system prompt. Pass role="<id>" to delegate / consensus / debate and the persona is prepended to your prompt. Five built-ins ship as package data: principal-reviewer, architect, debugger, security-reviewer, and explainer. A role_dirs directory adds new roles or overrides a built-in. list_roles enumerates the catalog.

Config. Rutherford works with zero config. When you do configure it, a TOML file at the global or project scope sets the agent roster, defaults, and safety policy; RUTHERFORD_* environment variables override specific fields. Full reference: docs/configuration.md.

Documentation

The name

.---------.
|  \/\/\/ |
|  O  [==]|
|    <    |
|  \___/  |
'---------'
-- Ensign Sam Rutherford --
USS Cerritos . Engineering

Named for the cheerful engineer aboard the USS Cerritos in Star Trek: Lower Decks, who has a gift for getting heterogeneous systems to cooperate. That is the job here: one agent hands work to a crew of others and brings the results back. Star Trek and Lower Decks are trademarks of their respective owners; this is an unaffiliated, fan-named open-source project.

Contributing

See CONTRIBUTING.md. The whole core is testable without a real agent; run just check before pushing, then just test-integration for whatever agents your machine has installed and authenticated.

License

MIT (c) John Chapman. See LICENSE.

Available Tools

19 tools
activityA

Show the background jobs IN FLIGHT right now (running + pending), each with a live elapsed time.

The focused "what is happening now" snapshot, distinct from list_jobs: where list_jobs enumerates every tracked job of every status (finished ones included), activity returns only the jobs still in flight -- {active: [...], count} with each row {job_id, tool, status, summary, started_at, elapsed_s}, longest-running first. Empty ({active: [], count: 0}) when nothing is running.

Inputs: no named parameters. Returns: result

analyzeA

Analyze the kept run corpus (read-only). report="historical_agreement" is the default and only report.

historical_agreement scans the consensus panels you kept (persist=true / default_persistence=job) and reports how often two DISTINCT model lineages reached the same verdict when they co-voted -- an OBSERVATIONAL signal for your roster choice (e.g. a lineage that never adds a dissent), NOT a vote discount: agreement is not correctness, so down-weighting agreeing lineages would punish them for being right together. An empty corpus returns an empty report whose notes explain how to build one.

Inputs: report. Returns: result

cancel_jobA

Cancel a running background job (killing its work) and return {job_id, status}; JOB_NOT_FOUND if unknown.

Cancelling an already-finished job is a no-op that returns its current status. The job's process tree is torn down on the next cancellation point.

Inputs: job_id (required). Returns: result

capabilitiesA

List the ACP agents Rutherford can drive (static roster; no spawn).

Each agent includes id, display name, launch command, provider, configured default_model / fallback_model, model_selection (launch_argv for Cursor-style launch flags, else in_session), and effort_capable. Model resolution is: explicit model -> agent default_model -> agent-native default. For live advertised model ids, use doctor(agent=<id>, connect_only=true) -- capabilities never probes an agent.

Inputs: no named parameters. Returns: result

consensusA

Ask the same prompt of several ACP agents in parallel and reduce the voices.

targets is a list of {cli, model} objects or cli / cli:model strings; each runs as its own ACP session concurrently. Omit targets, pass an empty list, pass the sentinel "all", or set expand_all=true to fan out to every registered agent (each at its default model, capped at max_targets); the result's skipped field explains any agent left out. Or name a saved panel (with optional panel_overrides) to reuse a stored roster + strategy instead of targets; they are mutually exclusive (see reload_panels). A {cli, model} target may also carry per-seat role / label / weight / parity / stance. With a strategy other than all-voices (unanimous | majority | plurality | weighted | parity-pair | rank, optionally with a verdict_schema), each voice is asked for a verdict and the panel collapses to one outcome (StrategyResult) instead of every voice. rank is a two-round protocol (F4b): every voice answers, then ranks the OTHER answers anonymized and self-excluded, aggregated by Borda mean-rank into a rank leaderboard with a pairwise agreement matrix and concordance; require_dissent surfaces each non-winning position on its dissent. discount_correlated=true (F3 vote-math, opt-in) down-weights correlated votes by model-family lineage (vendor fallback) so a panel of "one model in N CLI costumes" counts as one effective vote under majority / plurality / weighted (each voice's lineage_weight shows it). Optional stances (parallel to targets) steer each voice and cannot combine with the auto-expanded panel. synthesize (defaults to synthesize_default, off out of the box) adds a server-side combined answer (all-voices only); judge names the seat that writes it. timeout_s applies to every voice; one failing voice is a failed result, never an aborted panel. Consensus is read-only deliberation: a safety_mode beyond read_only (propose / write / yolo) is refused -- there is no coherent merge of edits from several agents into one tree -- so route write / propose work through delegate (a single agent isolated in a worktree sandbox). role names a persona (see list_roles) prepended to the prompt every voice receives. effort (low | medium | high | xhigh | max) asks every voice to spend more reasoning where it has a knob; max is accepted and clamped to each agent's ceiling. time_budget_s is a wall-clock deadline for the WHOLE panel (distinct from each voice's timeout_s): at the deadline answered voices are kept, in-flight ones cut, and the panel aggregates over the harvest if min_quorum usable remain (stop_reason="budget", with a rollup); below min_quorum is BUDGET_EXHAUSTED. on_budget is harvest | continue | resume (default default_on_budget). persist keeps the panel as a durable job (F2): a parent state.json linking a child record per voice, plus voices/voice-N.md artifacts; None follows default_persistence, true / false force it. mode="async" runs the panel as a background job and returns a job_id (poll with job_status / job_result); mode="sync" awaits it.

Inputs: prompt (required), mode, role, files, +20 more. Returns: result

continue_jobA

Continue a completed durable job with a new direction, picking up where the kept run left off.

job_id is the id of a kept run under <jobs_dir>/ (the run_dir name a persisted result carries). A delegate job resumes its one session (else re-injects the prior prompt + answer); a consensus panel resumes each voice's session and re-aggregates under the recorded strategy; a debate resumes each seat's session and argues rounds MORE rounds (rounds is ignored for the other kinds). The parent's record supplies the roster, model, working dir, role, files, and -- for a panel -- the strategy / stances / per-seat steering, all inherited unless overridden here. A seat whose agent cannot reload its ACP session is recorded as a failed voice, never silently dropped. The continuation is a fresh run linked to the parent (continued_from) -- the parent is never mutated. The trust gate is re-applied fresh and defaults to read_only (panels are read-only deliberation regardless). persist (default true) keeps the continuation as its own durable child job. mode="async" runs it as a background job and returns a job_id.

Inputs: job_id (required), prompt (required), mode, role, +9 more. Returns: result

debateA

Have several ACP agents argue a question across rounds and return the full transcript.

targets is a list of {cli, model} objects or cli / cli:model strings; a debate needs at least two. Or name a saved panel (with optional panel_overrides) for a stored roster instead of targets; they are mutually exclusive (rounds / judge stay call args). Each voice keeps ONE persistent ACP session across all rounds: round one is each voice's independent answer, and each later round shows a voice the others' latest positions and asks it to revise -- the agent remembers its own prior reasoning in-session, so only the delta is sent. carry_forward=true instead re-sends the FULL prior transcript verbatim each round (for a weaker session memory; bounded by time_budget_s). track_convergence=true asks each voice for a one-word verdict each round and stops early when the panel CONVERGES (a unanimous verdict) or STALLS (the decision holds for the configured tolerance); the outcome field reports the termination reason (converged / stalled / unresolved / budget / quorum_lost) and the final decision. synthesize=true (default) adds a closing summary; judge names a target to write it. A debate is read-only deliberation: a safety_mode beyond read_only (propose / write / yolo) is refused -- the voices run on persistent sessions in the working directory with no per-turn sandbox -- so route write / propose work through delegate (a single agent isolated in a worktree sandbox). role names a persona (see list_roles) prepended to the opening prompt every voice argues from. effort (low | medium | high | xhigh | max) asks every voice to spend more reasoning where it has a knob; max is accepted and clamped to each agent's ceiling. time_budget_s is a wall-clock deadline for the WHOLE debate enforced at round boundaries: a round still in flight at the deadline is cut and the transcript so far is finalized (stop_reason="budget", with a rollup); on_budget is harvest | continue | resume (default default_on_budget; continue runs every round to completion). persist keeps the debate as a durable job (F2): a parent state.json plus the full transcript.md; None follows default_persistence, true / false force it. mode="async" runs the debate as a background job and returns a job_id (poll with job_status / job_result); mode="sync" awaits it.

Inputs: prompt (required), mode, role, judge, +16 more. Returns: result

delegateA

Delegate a task to one ACP agent and return its normalized result.

cli is an agent id (see capabilities); model is optional (the agent's default otherwise). safety_mode is read_only | propose | write | yolo; when omitted, the configured default_safety_mode applies (read_only out of the box). write and yolo also need a trusted workspace (trust_workspace=true or a configured allowlist). direct_workspace_mutation=true asks for a write/yolo agent to edit working_dir itself, with live terminal access there, instead of an isolated worktree/temp copy — no diff is captured and nothing is applied back, so the run leaves no record of what it changed. Asking is not enough: the operator must have set allow_direct_workspace_mutation in config, working_dir must be explicit and on the configured trusted_workspaces allowlist (trust_workspace=true does NOT qualify), and it is refused inside a delegation chain. propose cannot use it at all (INVALID_INPUT). files lists paths to put in scope. role names a persona (see list_roles) whose system prompt is prepended to prompt. effort (low | medium | high | xhigh | max) asks the agent to spend more reasoning where it has a knob (codex via an advertised model[tier] id or a confirmed reasoning_effort config option; cursor via the model id; cline via --thinking; junie via env). max is accepted and clamped to the agent's ceiling where it has one. A reported no-op for an agent with none. Omitted, the configured default_effort (per-agent or global) applies. fallback is an ordered list of alternate targets (cli / cli:model strings or {cli, model} objects) tried when the primary fails on a re-execution-safe failure (a spawn/handshake failure that never ran the prompt); a benched alternate is skipped and fallback_chain records the path. A write/yolo delegation never falls back. allow_model_fallback (default true) first retries the same agent on its configured fallback model on a model-unavailable failure, where it has one. persist keeps this run as a durable job under <jobs_dir>/<run_id>/ (state.json + answer / diff artifacts); None follows default_persistence (ephemeral out of the box), true / false force it. session_id resumes a prior agent session: pass the session_id from an earlier delegate result and the agent reloads that conversation (ACP session/load) instead of starting fresh, so a follow-up turn continues it; agents that do not persist their own sessions fail RESUME_FAILED. mode="async" runs the turn as a background job and returns a job_id (poll with job_status / job_result); mode="sync" awaits it.

Inputs: cli (required), prompt (required), mode, role, +13 more. Returns: result

discoverA

Find installed ACP agents via the community registry and propose [agents.<id>] config for them.

The registry-driven companion to setup/doctor. It fetches the ACP agent registry (cached under ~/.rutherford/acp-registry.json for offline use), detects which registry agents are ALREADY installed here -- scanning PATH plus curated install dirs (~/.local/bin, ~/.cargo/bin, ~/.<vendor>/bin), never downloading or running npx -- and (with probe=true, the default) drives each found agent with a real read-only ACP round trip so the proposal only includes ones that actually answer. Returns the discovered agents and a proposed [agents.<id>] config block for the new drivers. write=true appends that block to the config for scope (project -> <cwd>/.rutherford/config.toml, global -> the platform path), creating the file if needed and never overwriting an existing section. refresh re-fetches the registry. Use this to adopt an ACP agent (or bridge) Rutherford does not ship as a built-in.

Inputs: probe, scope, write, refresh. Returns: result

doctorA

Probe each agent (or one named agent) with a real read-only ACP round trip and report conformance.

The trustworthy health check for ACP agents: whether each spawns, handshakes, and answers. Each report is ok / no_answer / model_unavailable / handshake_failed / auth_required / not_installed / error. auth_required means the agent is installed but holds no credential yet; sign it in once with login. model_unavailable means spawn + handshake succeeded (the agent is reachable) but the harness/provider rejected the model on the turn (a model/provider config issue, e.g. a Claude Code on AWS Bedrock / Vertex), so it is NOT reported as a broken agent. Slower than capabilities (it makes a real call per agent); run it to see which of the roster actually drive on this machine. connect_only runs the lighter handshake-only check (spawn + handshake, no prompt) and reports reachable / handshake_failed / auth_required / not_installed plus each agent's advertised models -- it shows whether Rutherford can talk to and configure an agent even when a model call would fail for a reason outside ACP (an auth / entitlement / quota issue, e.g. Grok without a SuperGrok subscription).

When an agent (codex / claude_code / pi) launches a separate npm ACP adapter shim and that shim is not installed but its underlying CLI is (you have codex/claude/pi), the report adds an install_hint with the exact npm i -g <package> command instead of a flat not_installed -- run that, or setup install_adapters=true, to set the adapter up.

Inputs: agent, timeout_s, connect_only. Returns: result

job_resultA

Return a finished background job's result envelope -- identical to the sync tool's envelope.

A succeeded job returns its stored result verbatim; a failed job returns its error; a cancelled or still-running job returns a structured error (poll job_status and retry); an unknown id is JOB_NOT_FOUND.

Inputs: job_id (required). Returns: result

job_statusA

Report one background job's status and timings (no heavy result); JOB_NOT_FOUND if the id is unknown.

status is pending | running | succeeded | failed | cancelled. Poll this, then call job_result once the job is succeeded (or to read the failure of a failed / cancelled job).

Inputs: job_id (required). Returns: result

list_jobsA

List the background jobs Rutherford is tracking (id, tool, status, summary, timestamps), newest first.

The light listing -- no heavy result. Fetch a finished job's result with job_result. Jobs are in-memory: a finished one is evicted after job_ttl_s, and a restart clears them all.

Inputs: no named parameters. Returns: result

list_rolesA

List the available role personas (id, name, description) for the role param.

A role is a reusable system prompt; pass its id as role="<id>" to delegate / consensus / debate and the persona is prepended to your prompt. Built-in roles ship with Rutherford; a role_dirs directory can add or override one.

Inputs: no named parameters. Returns: result

loginA

Sign an ACP agent in once, for an agent that doctor reports as auth_required.

Some agents open no session until a client has called ACP authenticate, then cache the credential themselves (Google Antigravity is one). No other Rutherford call signs in; this is the explicit place.

Without method it is read-only: status=authenticated if a session already opens, else status=method_required with the agent's advertised methods (id, name, kind). With method (an agent-kind id) it starts the sign-in as a background job, waits up to wait_s for the agent to print its sign-in link, and returns status=pending with job_id and signin_urls -- give the first link to the user, who completes the sign-in in a browser, then poll job_status / job_result. The job finishes authenticated once a session opens with the new credential (lifting any cooldown bench), fails with AUTH_FAILED (declined, the agent still refused a session afterwards, or no sign-in within timeout_s, which bounds the authenticate step), or with the agent's own handshake error if the confirming session fails for another reason. status=authenticated without method means a session opens and no ACP sign-in is needed; a turn may still need a provider key, which doctor checks. A repeated login while one is running returns that job (joined=true) instead of starting another (and status=cancelled if cancel_job ends it while the call waits); a different method then is refused with INVALID_INPUT until it finishes or is cancelled. The links are agent-authored, taken only from sign-in prompt lines, and never opened by Rutherford. An env_var method returns the variables to set (status=configure_env) and a terminal method returns the command to run (status=run_in_terminal); Rutherford never asks for or stores a credential value.

Inputs: agent (required), method, wait_s, timeout_s. Returns: result

planA

Ask one ACP agent for an implementation plan for goal under the architect persona (read-only).

A read-only delegate with the architect (planner) persona prepended: the agent designs an approach rather than implementing it. cli is an agent id (see capabilities); model is optional. files lists paths to put in scope. Always read-only -- planning never mutates the tree; implementing the plan is delegate in write mode.

Inputs: cli (required), goal (required), role, files, +3 more. Returns: result

reload_panelsA

Re-read saved panels from disk (after editing a panels.toon) and list those now available.

Returns {reloaded, count, panels: [{name, description, target_count}]}. Panels are discovered under ~/.rutherford/panels.toon, the project .rutherford/panels.toon, and $RUTHERFORD_CONFIG_DIR, merged by name (closest scope wins). A malformed panels file raises PANEL_INVALID naming the file and seat.

Inputs: no named parameters. Returns: result

reviewA

Review a diff or a set of files across one or more ACP agents (read-only). Provide diff or paths.

A read-only consensus under the principal-reviewer persona: each agent reviews the code and the panel returns every voice plus a combined verdict. targets is a list of {cli, model} objects (or cli / cli:model strings); or name a saved panel (with optional panel_overrides) instead -- the two are mutually exclusive. Provide diff (a unified diff, inlined into the prompt) or paths (files put in scope for the agents to read). synthesize defaults on (the combined verdict); pass false for the raw per-voice reviews. Always read-only -- a review never mutates the tree.

Inputs: diff, role, panel, paths, +5 more. Returns: result

setupA

Show where config lives and scaffold a starter config.toml; the first-run helper.

scope is project (<cwd>/.rutherford/config.toml) or global (the platform config dir's config.toml). It returns the proposed starter content (the most useful settings at their effective defaults) and the resolved path, plus a snapshot of the agents you already have. Pass write=true to create the file -- it never overwrites an existing one (already_exists=true, written=false). trust_workspace=true adds the current directory to trusted_workspaces so write/yolo delegations are permitted there.

The adapters block reports agents whose underlying CLI is installed but whose npm ACP adapter shim is not (codex needs codex-acp, claude_code needs claude-agent-acp, pi needs pi-acp -- what doctor flags as not_installed with an install hint). Pass install_adapters=true to run npm i -g <package> for each of those automatically (an explicit, opt-in machine change; off by default).

Inputs: scope, write, trust_workspace, install_adapters. Returns: result

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

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    TDQS

    A4.3/5.0

    Scored across 19 tools

    Disambiguation4/5

    Most tools target clearly distinct operations: delegation, multi-agent consensus, debate, jobs, setup, and diagnostics. The main overlap is deliberate: `plan` is a specialized `delegate`, and `review` is a specialized read-only `consensus`, while `list_jobs`, `activity`, `job_status`, and `job_result` are closely related but explicitly contrasted in their descriptions.

    Naming Consistency4/5

    All names use consistent snake_case with no camelCase or casing chaos. They are mostly readable and predictable, though some are bare verbs/nouns (`delegate`, `consensus`, `doctor`) rather than uniformly verb_noun.

    Tool Count3/5

    Nineteen tools is borderline heavy for a single server, driven by separate surfaces for delegation, deliberation, jobs, agent diagnostics, setup, discovery, and panels. Each tool has a role, but the set is broad enough that an agent must navigate many adjacent operations.

    Completeness4/5

    The surface covers the main lifecycle well: agent discovery/authentication/health, roles, delegation, planning, consensus, debate, review, job polling/cancellation/continuation, and setup. Minor gaps remain around explicit panel CRUD/session management, but core workflows are not dead-ended.

    Maintenance

    ActivityMaintained
    ResponsivenessLimited data

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