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consult-mcp

MCP server orchestrating local CLI agents (Claude Code, OpenAI Codex, Google Gemini) for cross-validation, second opinions, and persona-driven prompting.

What it does

When you're working in Claude Code (or any MCP client), consult-mcp lets you ask other LLM CLIs for their take — without leaving the conversation. Use cases:

  • Second opinion: "Claude wrote this — what does Gemini think?"

  • Cross-validation: send the same question to claude/codex/gemini in parallel and compare

  • Variant generation: pass ["claude", "claude"] for two independent responses to the same prompt

  • Specialized framing: apply a persona (architect, reviewer, researcher, coder) to focus the model

Eighteen MCP tools ship in v0.10:

  • Read-only single-shot (no file mutation, return immediately):

    • consult(agent, prompt, persona?, timeout_seconds?) — single agent

    • consult_parallel(agents, prompt, persona?, timeout_seconds?) — fan-out to N agents

    • codereview(agents, files, focus?, timeout_seconds?) — multi-agent code review with structured findings

    • consensus(agents, question, stances?, synthesizer?, timeout_seconds?) — multi-agent verdict with optional stance steering

    • challenge(agent, claim, timeout_seconds?) — anti-sycophancy single-agent pushback

  • Async debate (returns debate_id immediately, runs in background):

    • debate_start(agents, topic, max_turns?, history_window?, terminator?, ...) — kick off round-robin debate

    • debate_status(debate_id) — poll progress + transcript

    • debate_cancel(debate_id) — request soft cancellation

    • debate_list(active_only?, limit?) — list active + archived debates

    • debate_replay(debate_id) — full transcript from memory or SQLite archive

    • debate_export(debate_id, format?, truncate_body_chars?) — render archived debate as portable markdown (default) or stable v1 JSON for Obsidian/Notion/programmatic consumers

  • Synchronous streaming debate (foreground call with progress notifications):

    • debate_run(agents, topic, max_turns?, ...) — returns when the loop terminates; pushes per-turn progress to MCP clients that honour progressToken (e.g. Claude Code). Non-resumable — for long debates use debate_start + poll instead

  • Atomic deliberation (3-stage in one call):

    • council(agents, question, chairman?, persona?, timeout_seconds?) — independent → cross-rank (anonymized) → synthesis

  • Niche (focused single-purpose tools):

    • planner(agent, problem, depth?, timeout_seconds?) — structured task decomposition (JSON tasks with dependencies)

    • diff_review(agents, diff_text?|git_ref?, cwd?, focus?, ...) — review a git diff for risks/regressions

    • apilookup(query, agent?, timeout_seconds?) — current docs lookup with web search (default agent: gemini)

  • File-mutating (activates CLI permission/sandbox bypass flags):

    • implement(agent, plan, base_path, constraints?, timeout_seconds?) — delegate code changes; returns diff

    • delegate_implementation(task, base_path, planner_agent?, implementer_agent?, reviewer_agents?, ...) — composite plan→implement→review in one call. Plan via planner_agent, write code via implementer_agent (mutation rights, same CONSULT_MCP_ALLOWED_BASE guard), then fan-out to reviewer_agents (auto-routes to diff_review for git diffs or codereview for mtime-mode workspaces). Default reviewers exclude the implementer.

Related MCP server: personal-mcp

Prerequisites

  • Python 3.10+ (the server itself)

  • uv for installation (pipx install uv or follow astral.sh/uv)

  • At least one of these CLI tools installed and authenticated:

    • Claude Code CLI — install via claude.com/code, then claude login

    • OpenAI Codex CLI — npm install -g @openai/codex, set OPENAI_API_KEY

    • Google Gemini CLI — install via geminicli.com, authenticate per docs

You don't need all three — consult-mcp reports per-agent status and skips missing CLIs.

API keys

Each CLI handles its own auth. Common env-var setup:

Platform

Set env var

Windows (PowerShell, persistent)

setx OPENAI_API_KEY "sk-..."

Windows (current shell)

$env:OPENAI_API_KEY = "sk-..."

macOS / Linux (current shell)

export OPENAI_API_KEY="sk-..."

macOS / Linux (persistent)

append export OPENAI_API_KEY="sk-..." to ~/.bashrc or ~/.zshrc

Replace OPENAI_API_KEY with GEMINI_API_KEY for Gemini. Claude Code uses interactive login (claude login); no env var.

Installation

Add this to your MCP client's configuration. For Claude Code, that's .mcp.json (project-local) or ~/.claude.json (global):

{
  "mcpServers": {
    "consult": {
      "command": "uvx",
      "args": [
        "--from",
        "git+https://github.com/oblogin/consult-mcp.git",
        "consult-mcp"
      ]
    }
  }
}

Restart your MCP client. All six tools (consult, consult_parallel, codereview, consensus, challenge, implement) should appear.

A copy-pasteable snippet is in examples/.mcp.json.

Quick start

// Single-agent consultation:
consult({
  "agent": "gemini",
  "prompt": "Should we use GAS for an inventory system in Unreal Engine?",
  "persona": "architect"
})
// → {
//     "status": "success",
//     "agent": "gemini",
//     "persona": "architect",
//     "response": "GAS overkill for simple inventory; trade-offs ...",
//     "metadata": { "duration_seconds": 8.4, "returncode": 0 }
//   }

// Parallel cross-validation:
consult_parallel({
  "agents": ["claude", "codex", "gemini"],
  "prompt": "Reply with just the digit: what is 2+2?",
  "persona": "default"
})
// → {
//     "status": "success",
//     "responses": [
//       { "agent": "claude", "status": "success", "response": "4", ... },
//       { "agent": "codex",  "status": "success", "response": "4", ... },
//       { "agent": "gemini", "status": "success", "response": "4", ... }
//     ],
//     "summary": { "total": 3, "succeeded": 3, "failed": 0, "wall_time_seconds": 9.1, "max_duration_seconds": 8.4 }
//   }

Specialized tools (v0.2)

codereview — multi-agent code review

codereview({
  "agents": ["codex", "gemini"],
  "files": ["src/auth.py", "src/auth_test.py"],
  "focus": "auth and session handling"
})
// → { "status": "success",
//     "reviews": [
//       { "agent": "codex", "status": "success", "response": "...",
//         "findings": [
//           {"severity": "high", "location": "src/auth.py:42",
//            "title": "Missing CSRF check", "description": "..."}
//         ]},
//       { "agent": "gemini", ... }
//     ],
//     "summary": { "succeeded": 2, ... } }

Each agent is invoked with the reviewer persona, which instructs it to return JSON {summary, findings: [{severity, location, title, description}]}. The tool parses that JSON; on parse failure, the raw response stays in reviews[i].response with a metadata.findings_parse_error flag.

consensus — multi-agent verdict with stance steering

consensus({
  "agents": ["claude", "codex", "gemini"],
  "question": "Should we adopt SQLite WAL mode for our writes?",
  "stances": ["for", "against", "neutral"],
  "synthesizer": "claude"
})
// → { "votes": [{...}, {...}, {...}],
//     "synthesis": { "agent": "claude", "response": "Both sides agree..." } }

Stances (for/against/neutral) prefix each agent's prompt. Optional synthesizer runs once more after the votes to produce a verdict.

challenge — anti-sycophancy pushback

challenge({
  "agent": "claude",
  "claim": "Premature optimization is always wrong; ignore performance until benchmarks fail."
})
// → { "agent": "claude", "persona": "skeptic",
//     "response": "Counter: in real-time loops, even microseconds matter; ..." }

Persona is hardcoded to skeptic. The agent is instructed to find weaknesses and counter-arguments rather than agree.

implement — delegate code changes ⚠️ mutation-capable

implement({
  "agent": "codex",
  "plan": "Add a /healthz endpoint to api/server.py returning {\"ok\": true}.",
  "base_path": "F:/repos/my-app",
  "constraints": "Don't modify tests/. Use existing FastAPI app."
})
// → { "status": "success",
//     "mode": "git",
//     "files_modified": ["api/server.py"],
//     "files_created": [],
//     "diff": { "text": "...", "stat": "1 file changed, 5 insertions(+)", ... } }

This tool activates CLI mutation flags (--permission-mode acceptEdits, --dangerously-bypass-approvals-and-sandbox, --yolo). If base_path is a git repo → unified diff returned. If not → file list only (mtime detection). See Security & Limitations below before using.

Async debate (v0.3)

For long deliberation between 2-6 agents — round-robin, runs in the background, transcript persists to SQLite for replay.

When to use vs council

council

debate_*

Latency

Sync, ~min wait

Async, runs minutes-to-hours

Stages

3 (independent → rank → synthesis)

N round-robin turns

Cancel

n/a

debate_cancel(id)

Persistence

Transcript in response

Auto-saved to ~/.consult-mcp/archive.db

Best for

Quick verdict with explicit ranking

Open-ended debate where agents react to each other

Quick example

// Start a debate; returns id immediately:
debate_start({
  "agents": ["claude", "codex", "gemini"],
  "topic": "Should we move our analytics from PostgreSQL to ClickHouse?",
  "max_turns": 10,
  "history_window": 6,
  "terminator": "any"
})
// → { "status": "success", "debate_id": "abc123...", "started_at": "..." }

// Poll progress (call as often as you like):
debate_status({ "debate_id": "abc123..." })
// → { "state": "running", "turn_count": 3, "transcript": [...] }

// When state == "completed":
// → { "state": "completed", "terminated_by": "done", "turn_count": 7, "transcript": [...] }

// Or cancel early:
debate_cancel({ "debate_id": "abc123..." })
// → { "already_finished": false, "requested_at": "..." }

// List debates (memory + archive):
debate_list({ "limit": 20 })

// Replay an old debate from SQLite:
debate_replay({ "debate_id": "abc123..." })

// Export as portable markdown (Obsidian-friendly frontmatter + transcript):
debate_export({ "debate_id": "abc123..." })
// → { "status": "success", "format": "md", "content": "---\nschema_version: 1\n..." }

// Or as stable JSON for programmatic consumers:
debate_export({ "debate_id": "abc123...", "format": "json" })
// → { "status": "success", "format": "json", "content": { "schema_version": 1, "turns": [...] } }

// Long transcripts: truncate per-turn bodies to fit MCP transport limits:
debate_export({ "debate_id": "abc123...", "truncate_body_chars": 2000 })

Export format

debate_export returns either markdown (default, copy-pasteable into Obsidian/Notion) or stable JSON. The JSON shape is versioned via schema_version: 1; future breaking changes bump the version. Markdown frontmatter is generated through yaml.safe_dump, so user-controlled fields (topic, agent_name, error_message) cannot break it through :, \n or ---. Total response size is capped at 5 MiB — pass truncate_body_chars=N to fit larger transcripts. All five debate states (pending, running, completed, cancelled, error) are exportable; running snapshots are explicitly marked.

Terminator semantics

The terminator controls soft early-stop (DONE marker emitted by the agent). Hard caps (max_turns, external cancel, all_slots_down) are unconditional.

Spec

Behavior

"any" (default)

OR(max_turns, done) — stops on either

"max_turns_only"

Ignore DONE; always run to max_turns

"done_only"

Stop only on DONE (still bounded by max_turns hard cap)

{"and": ["max_turns", "done"]}

Custom JSON expression

DONE detection is word-boundary aware: "abandoned" does NOT match, "...DONE" does.

Council — atomic 3-stage analysis

Single MCP call, ~min latency. Pattern from llm-council-mcp:

council({
  "agents": ["claude", "codex", "gemini"],
  "question": "Should we move analytics to ClickHouse?",
  "chairman": "claude"   // default = first agent
})
// → { "status": "success",
//     "stage1": [...],   // independent answers (parallel)
//     "stage2": [...],   // each agent ranks the anonymized responses
//     "stage3": { ... }, // chairman synthesizes
//     "stage2_parse_summary": { "json": 2, "fuzzy": 1, "unparseable": 0 } }

Stage 2 anonymizes responses as Response A, Response B, etc. so agents rank by content quality, not by author.

Niche tools (v0.4)

planner — structured task decomposition

planner({
  "agent": "claude",
  "problem": "Migrate the API from REST to gRPC, keeping the existing auth flow.",
  "depth": "tree"
})
// → { "status": "success", "agent": "claude",
//     "plan": {
//       "summary": "Phased migration, 8 tasks",
//       "tasks": [
//         {"id":"T1","title":"Define proto schema","depends_on":[],"estimated_size":"M"},
//         {"id":"T2","title":"Generate stubs","depends_on":["T1"],"estimated_size":"S"},
//         ...
//       ]
//     },
//     "depth": "tree" }

Pass depth="flat" to force depends_on=[] for every task. On JSON parse failure, the tool returns parse_error: true with raw_response preserved.

diff_review — git diff regression review

// With raw diff text:
diff_review({
  "agents": ["claude", "gemini"],
  "diff_text": "diff --git a/auth.py b/auth.py\n@@ ...",
  "focus": "security regressions"
})

// Or pulling from a git repo directly:
diff_review({
  "agents": ["claude"],
  "git_ref": "HEAD~3..HEAD",
  "cwd": "F:/repos/my-app"
})

Mutually exclusive: pass either diff_text (raw) OR git_ref + cwd. The reviewer persona is hardcoded.

apilookup — current-docs lookup

apilookup({
  "query": "Latest Anthropic Python SDK version + breaking changes vs 1.x"
})
// → { "agent": "gemini", "persona": "researcher_current",
//     "response": "As of 2026-04, the SDK is at 2.x ..." }

Default agent is gemini (web search built into the headless CLI). Other agents fall back to training-data answers and flag the staleness.

Personas

Eight built-in system prompts ship in v0.4:

Persona

Use case

default

Neutral helpful assistant

architect

Design, trade-offs, system structure

reviewer

Bugs, edge cases, security — returns severity-tagged JSON findings

researcher

Surveys alternatives, best practices, reference implementations

researcher_current

Same focus + emphasizes current docs / web sources / dates

coder

Minimal practical code, no over-engineering

skeptic

Anti-sycophancy — finds weaknesses, edge cases, counter-arguments

planner

Structured task decomposition — outputs JSON task tree

Adding your own

Create a markdown file at ~/.consult-mcp/personas/<name>.md:

---
name: security_reviewer
description: Focuses on auth, crypto, and OWASP top 10
---

You are a security-focused code reviewer. Concentrate on auth flaws,
crypto misuse, injection vectors, and OWASP top-10 risks. Skip generic
style feedback. Output severity-tagged findings as JSON.

It's available immediately after the next server restart: consult({"agent":"claude","prompt":"...","persona":"security_reviewer"}).

The full file format, length limits, naming policy and parser-error matrix are documented in Docs/persona-file-contract.md. User personas in ~/.consult-mcp/personas/ override built-ins on name collision — be explicit if that's what you want.

Community pack

A small curated set of ready-to-copy personas lives in examples/personas/community/ — currently security_reviewer, perf_reviewer, and regex_explainer. Pick what you want and cp it into ~/.consult-mcp/personas/. Names are guaranteed not to clash with built-ins. New PRs welcome — see the community README for contributing rules and the validator (python -m scripts.validate_personas examples/personas/community) that runs in CI.

Configuration

Built-in CLI configs live in the package (read-only). To override the command, args, or timeout for any agent — drop a JSON file at ~/.consult-mcp/agents/<name>.json matching the schema:

{
  "name": "claude",
  "command": ["claude"],
  "internal_args": ["--print", "--model", "opus"],
  "timeout_seconds": 180,
  "agent_class": "consult_mcp.agents.claude.ClaudeAgent"
}

User overrides replace the built-in entirely (no merging). Restart the MCP client to pick up changes.

Troubleshooting

Symptom

Likely cause

Fix

error.type: unknown_agent

CLI binary not in PATH

where claude (Windows) / which claude (Unix); install missing CLI

error.type: timeout

CLI took longer than 120s

pass timeout_seconds to the tool, or override timeout_seconds in ~/.consult-mcp/agents/<name>.json

error.type: cli_error with stderr "API key"

Missing OPENAI_API_KEY / GEMINI_API_KEY

set the env var (see API keys section)

error.type: cli_error with stderr "not logged in"

Claude Code not authenticated

run claude login once interactively

error.type: cli_error with stderr about model

Account/CLI version mismatch

upgrade the CLI: npm i -g @openai/codex@latest etc.

Server starts but no tools shown

Restart MCP client after install or .mcp.json edits

full restart (not just reload)

ImportError on Python 3.9

Python too old

python --version ≥ 3.10 required

⚠️ Security & Limitations

Read-only by default. consult, consult_parallel, codereview, consensus, and challenge invoke CLIs without mutation/sandbox-bypass flags. Agents return text answers; they do not edit files or execute commands.

implement is the only mutation-capable tool (v0.2). It activates --permission-mode acceptEdits (Claude), --dangerously-bypass-approvals-and-sandbox (Codex), and --yolo (Gemini). A malicious or careless prompt can delete files, exfiltrate secrets, or run arbitrary commands. Run implement in isolated repositories and code-review the resulting diff before trusting it. Mutation flags are kept in a separate mutation_args field per agent config and only applied when implement is called — they cannot leak into other tools.

Local-only. consult-mcp runs as a single process on a single machine. No cross-machine coordination, no daemon, no shared state.

Privacy. Prompts and responses pass through whichever LLM provider you've configured per CLI (Anthropic, OpenAI, Google). Don't send data you wouldn't paste into the respective web UIs. The persona system prompt is appended to every request.

Restart loss. Active debates (state in {pending, running}) live only in memory. Restarting the MCP client kills any in-flight debate — the asyncio task is gone, no resume, the transcript up to that point is NOT archived (archive only writes on terminal state). Completed debates are persisted to ~/.consult-mcp/archive.db and replayable via debate_replay.

Resource limits. debate_start rejects new starts when ≥ 5 debates are already active (override via CONSULT_MCP_MAX_ACTIVE_DEBATES env). This is a guard against accidental fork-bomb when multiple chained tool calls trigger debate creation.

Privacy of archive. ~/.consult-mcp/archive.db is plain SQLite, not encrypted. Anyone with file-system access can read transcripts. Don't run debates on data you wouldn't write to a plain file.

Roadmap

Iteration

Focus

Status

IT-001

MVP — consult, consult_parallel, 5 personas

✅ shipped (v0.1)

IT-002

Specialized — codereview, consensus, challenge, implement

✅ shipped (v0.2)

IT-003

Async debate — debate_*, council, SQLite archive

✅ shipped (v0.3)

IT-004

Niche — planner, diff_review, apilookup

✅ shipped (v0.4)

IT-006

Markdown export — debate_export

✅ shipped (v0.6)

IT-007

Community personas pack + persona-file contract + validator

✅ shipped (v0.7)

IT-008

Streaming — debate_run, council progress + cancellation

✅ shipped (v0.8)

IT-010

Composite — delegate_implementation (plan→implement→review)

✅ this release (v0.10)

What's next

  • Streaming progress notifications for async debates (MCP SSE)

  • Web UI / dashboard for archived debate replay

  • Community personas (PRs welcome)

  • Documentation site (Sphinx/MkDocs) once tool count > 15 or README > 800 lines

Detailed iteration plans live in Docs/plans/iterations/.

License

MIT — see LICENSE.

Available Tools

18 tools
apilookupA

Look up current documentation for an API/library/SDK using web-capable CLI.

Use cases:

  • Verify an SDK's current version + breaking changes before upgrading

  • Find the canonical doc URL for a feature you only half-remember

  • Spot deprecations introduced in the last 12 months

Default agent is gemini (web search built in via the headless CLI). Other agents will answer from training data and flag the staleness in their response.

Inputs: query (required), agent, timeout_seconds.

challengeA

Push back on a claim — agent with skeptic persona finds counter-arguments.

Use cases:

  • Anti-sycophancy: counterweight to consultations that always seem to agree

  • Sanity-check a design before committing to it

  • Surface failure modes you might have missed

The persona is fixed to skeptic; passing a different persona is not allowed (would defeat the tool's purpose).

Inputs: agent (required), claim (required), timeout_seconds.

codereviewA

Cross-agent code review.

Pattern: 'Claude implemented → Codex and Gemini review the code'. Sends file contents to N agents in parallel with reviewer persona. Each agent's response is parsed into severity-tagged findings; raw text is preserved in response for any unparseable cases.

Use cases:

  • Validate Claude's code via Codex + Gemini perspectives

  • Surface bugs / edge cases / security issues

  • Identify regressions before merging

Inputs: agents (required), files (required), focus, timeout_seconds.

consensusA

Multi-agent verdict with optional stance assignment + optional synthesis.

Use cases:

  • Force productive disagreement: stances=["for", "against", "neutral"]

  • Lightweight cross-validation when debate is overkill (one round per agent)

  • Explicitly named perspectives instead of implicit consensus

Distinct from consult_parallel because each agent can get a stance-steered prompt; distinct from debate (IT-003) because it's one round, not round-robin.

Inputs: agents (required), question (required), stances, persona, +2 more.

consultB

Send a prompt to one CLI agent (claude/codex/gemini) and return its response.

Use cases:

  • Quick second opinion on an idea or design

  • Ask a specific model for its take on a problem

  • Get help from an agent specialized via persona

Available agents: claude, codex, gemini. Available personas: default, architect, reviewer, researcher, coder.

Inputs: agent (required), prompt (required), persona, timeout_seconds.

consult_parallelA

Fan-out the same prompt to multiple CLI agents in parallel.

Use cases:

  • Cross-validate: ask claude, codex, and gemini the same question

  • Variant generation: pass ["claude", "claude"] for two independent responses

  • Collect diverse perspectives on a design or claim

Wall time = max(per-agent latency), not sum. Duplicates are NOT deduplicated — each entry runs independently (intentional, supports variant generation).

Inputs: agents (required), prompt (required), persona, timeout_seconds.

councilA

3-stage council: independent → cross-rank (anonymized) → synthesis.

Use cases:

  • Atomic deliberation when you don't want to manage poll/cancel state

  • 3-perspective review with explicit ranking step (reduces first-mover bias)

  • Quick consensus that's stronger than consult_parallel but lighter than debate

council_id registers a cancellation watermark with CancellationRegistry. To cancel an in-flight council, the caller must supply the id upfront and then bump the counter via CancellationRegistry.request_cancel(id) from another in-process caller. The MCP-exposed debate_cancel tool does NOT cover council ids — it looks up DebateStore which has no council entries. Cancellation is honoured between stages only; running subprocesses are never killed mid-stage.

ctx is the FastMCP-injected context. When the client supports progress notifications it sees three events (one per stage); otherwise emit is a silent no-op.

Returns a dict with status ∈ {success, cancelled, failed} plus partial: True when results are degraded (some stage1 vote failed, or stage3 chairman failed). failed is reserved for "all stage1 voters failed" — the council had nothing to deliberate on.

Inputs: agents (required), question (required), chairman, persona, +3 more.

debate_cancelA

Request cancellation of a running debate. Returns immediately.

If the debate is already finished (completed / cancelled / error), this is a no-op and returns already_finished=true. The loop polls the cancellation flag between turns, so cancellation may take up to one turn-latency to land.

Inputs: debate_id (required).

debate_exportA

Render an archived/active debate as portable markdown or JSON.

format:

  • "md" — YAML-frontmatter + transcript markdown (default)

  • "json" — stable ExportPayload v1 dict

truncate_body_chars shortens per-turn body to at most N characters (suffix "... (truncated)" added). Use to keep response under MCP transport limits when transcripts are large.

Inputs: debate_id (required), format, truncate_body_chars.

debate_listA

List debates, sorted by started_at desc.

With active_only=True: only in-memory debates in pending/running state. Otherwise: merge in-memory + archive (memory wins on id collision), then sort.

Inputs: active_only, limit.

debate_replayC

Return full transcript for a debate (memory first, then archive).

Inputs: debate_id (required).

debate_runA

Run an async round-robin debate to completion, streaming progress.

Same arguments as debate_start plus the FastMCP-injected ctx. Returns when the loop terminates (max_turns / done / cancel / all_slots_down / error). Per-turn progress is emitted via ctx.report_progress if the client supports it (silently no-op otherwise).

Return shape (IT-008/C-01 taxonomy):

  • status: "success" — debate completed normally

  • status: "cancelled" — external debate_cancel honoured between turns

  • status: "failed" — agent registry not initialised, all slots down, zero successful turns, or unhandled exception in the loop

Inputs: agents (required), topic (required), max_turns, history_window, +4 more.

debate_startA

Start an async round-robin debate. Returns debate_id immediately.

The loop runs in the background; poll debate_status(debate_id) for progress and final transcript. Use debate_cancel(debate_id) to abort early.

Use cases:

  • Long deliberation between 2-6 agents (each round ≈ per-agent latency)

  • When you want to step away and check back later

  • Need a transcript saved for replay (auto-archived in SQLite on completion)

Inputs: agents (required), topic (required), max_turns, history_window, +3 more.

debate_statusB

Get current status of a debate (pending/running/completed/cancelled/error).

Inputs: debate_id (required).

delegate_implementationA

Plan → implement → review in one MCP call.

The composite tool runs three stages sequentially:

  1. Plan via the planner tool (planner_agent).

  2. Implement via the implement tool (implementer_agent; mutation flags enabled). base_path must be allow-listed via CONSULT_MCP_ALLOWED_BASE exactly as for implement.

  3. Review via diff_review or codereview (reviewer_agents, in parallel). Choice is automatic based on implement's output: a unified git diff routes to diff_review; otherwise the list of modified files routes to codereview.

Returns one of:

  • {"status": "success", ...} — all three stages ok

  • {"status": "partial_success", ...} — implement ok, ≥1 reviewer failed or review skipped

  • {"status": "partial_error", "stage_failed": "implement", ...} — implement failed; review run best-effort against any partial diff

  • {"status": "error", "stage_failed": "plan", ...} — planner failed, downstream stages skipped

The tool never raises — all errors are surfaced as structured fields.

Inputs: task (required), base_path (required), planner_agent, implementer_agent, +6 more.

diff_reviewA

Review a git diff for risks, regressions, and breaking changes.

Pass either diff_text (raw unified diff) OR git_ref + cwd (the tool runs git diff <ref> in cwd for you). Mutually exclusive.

Use cases:

  • Pre-merge sanity check on a PR's diff

  • Spot accidental breaking changes when refactoring

  • Cross-validate a branch against multiple reviewer agents

Inputs: agents (required), diff_text, git_ref, cwd, +2 more.

implementA

Delegate implementation to a CLI agent that can edit files in base_path.

Use cases:

  • 'Claude designs → Codex implements → Claude+Gemini review' workflow

  • Apply a refactor proposal across files without manual edits

  • Hand off boilerplate work to a different model

Activates the agent's mutation flags (e.g. --permission-mode acceptEdits for Claude). The tool returns a diff of files the agent created/modified/deleted.

base_path MUST be an absolute path. A relative path is resolved against the MCP server process's cwd (NOT the calling user's terminal cwd), which is rarely what the caller intends and may land in an unexpected directory.

If base_path is a git repo: full unified diff is returned. If not: only the list of changed files (mtime-detected, no diff text).

Inputs: agent (required), plan (required), base_path (required), constraints, +1 more.

plannerA

Decompose a problem into atomic tasks with optional dependencies.

Use cases:

  • Break a feature request into ordered work items before implementation

  • Surface parallelizable branches in a multi-step task

  • Get a starting structure that the orchestrator can iterate on

depth="flat" returns a flat list (depends_on=[] always); depth="tree" (default) lets the agent model dependencies for parallel execution.

Inputs: agent (required), problem (required), depth, timeout_seconds.

Tool Schema Changelog

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

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    TDQS

    A3.8/5.0

    Scored across 18 tools

    Disambiguation5/5

    Each tool targets a distinct workflow or function, from single-agent consult to multi-stage debate and code implementation. Descriptions clarify nuances between similar tools (e.g., consult_parallel vs. consensus vs. council), leaving no ambiguity.

    Naming Consistency5/5

    All tool names follow a consistent snake_case verb_noun pattern (e.g., consult_parallel, debate_run, delegate_implementation). The convention is uniform and predictable across all 18 tools.

    Tool Count4/5

    At 18 tools, the server is ambitious but well-scoped for its domain of multi-agent orchestration and code assistance. While extensive, each tool earns its place with specific use cases; the count does not feel excessive for the breadth of functionality.

    Completeness5/5

    The tool surface covers the full lifecycle of agent interactions: quick consult, parallel fan-out, structured consensus, multi-round debate with replay/export, planning, implementation, and code review. No obvious gaps exist for the stated purpose of MCP-based consulting.

    Maintenance

    ActivityInactive
    ResponsivenessNo recent community issues

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