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yukinuma-cpu

agent-bridge-mcp

by yukinuma-cpu

agent-bridge-mcp

A capability-aware MCP server and HTTP/WebSocket gateway for orchestrating interchangeable coding agents.

Agent Bridge treats each agent as an adapter behind a common runtime contract. The core router does not hard-code Claude, Codex, or Antigravity behavior; registered adapters advertise capabilities such as sessions, streaming, cancellation, model selection, sandbox control, file tools, and shell tools. Workflows may name a specific agent or select one by required capabilities.

Status: experimental. Interfaces may still change. The runtime is intended for trusted local development environments and should not be exposed to untrusted networks.

Architecture

MCP / HTTP / WebSocket
        |
        v
  SessionRouter
        |
        v
   AgentRegistry
        |
   AgentAdapter
   /    |       \
Claude Codex  Antigravity  ...
        |
        +--> TaskManager
        +--> SessionStore

WorkflowEngine ----> EvidenceGate ----> Git / tests / typecheck / lint
     |
     +--> ReviewLoop preset

The built-in adapters currently cover:

  • Claude Code CLI

  • Codex CLI

  • Codex SDK

  • Antigravity (agy) CLI

Additional agents can be added by implementing and registering another AgentAdapter; the core AgentType is not a closed union of built-in names.

Related MCP server: agent-intern

Core concepts

Agent Registry and capabilities

Each registered adapter declares:

  • sessions

  • streaming

  • cancellation

  • models

  • sandboxControl

  • fileTools

  • shellTools

Call agent_capabilities over MCP or GET /api/capabilities over HTTP to inspect what is available.

A workflow can select a concrete adapter:

- type: agent
  role: implementer
  agent: codex
  engine: cli

or request capabilities and let the registry choose:

- type: agent
  role: implementer
  requires:
    - sessions
    - fileTools
    - shellTools

Generic workflows

WorkflowEngine executes ordered role-based steps. An agent step can receive:

  • {{input}}

  • {{previousOutput}}

  • {{evidenceSummary}}

  • {{gitDiff}}

  • {{testResults}}

Evidence steps are fail-closed: no verification commands means no verified PASS.

The older implement → evidence → review loop remains available as a compatibility preset on top of the generic workflow runtime. Implementer and reviewer are selectable registered agents rather than fixed core dependencies.

Sessions and tasks

Agent Bridge tracks internal sessions and external agent session/thread/conversation IDs. Matching considers agent, engine, workspace, project, topic, and task type. Explicit session reuse is rejected when the requested agent/engine/workspace is incompatible.

Every dispatch creates a task record with status, output, error, and exit code. Cancellation is terminal; late completion cannot resurrect a cancelled task.

Install

npm install -g @yukinuma/agent-bridge-mcp

Requires Node.js 20+ and whichever agent CLIs you intend to drive already installed and authenticated.

Antigravity on Windows

agy expects a real terminal. On Windows the adapter runs it under winpty when available and keeps stdin open for the call. It persists the returned conversation ID and resumes with --conversation on later turns.

Set WINPTY_PATH or AGY_PATH if either binary is in a non-standard location. Non-Windows Antigravity execution is not yet well tested.

Use as an MCP server

{
  "mcpServers": {
    "agent-bridge": {
      "command": "agent-bridge-mcp",
      "env": {
        "AGENT_BRIDGE_WORKSPACE": "/path/to/your/projects"
      }
    }
  }
}

MCP tools:

Tool

Purpose

agent_send

Dispatch to any registered agent/engine

agent_capabilities

List adapters or find capability matches

agent_status

Inspect a task

agent_sessions

List tracked sessions

agent_cancel

Cancel a task

agent_evidence_check

Run fail-closed repository verification

agent_workflow

Execute a generic role-based workflow

agent_review_loop

Run the compatibility implement/review preset

Use as an HTTP/WebSocket gateway

export ABC_AUTH_TOKEN="$(openssl rand -hex 24)"
export AGENT_BRIDGE_WORKSPACE="/path/to/your/projects"
agent-bridge-gateway

The gateway refuses to start without ABC_AUTH_TOKEN.

Variable

Default

Meaning

ABC_AUTH_TOKEN

(required)

Shared secret for REST and WebSocket auth

PORT

3030

Listening port

AGENT_BRIDGE_HOST

127.0.0.1

Bind address

AGENT_BRIDGE_WORKSPACE

process.cwd()

Root boundary for execution targets

AGENT_BRIDGE_ROOT

process.cwd()

Session/task state directory

AGENT_BRIDGE_ALLOWED_ORIGINS

localhost only

Comma-separated CORS allowlist

HTTP endpoints

Method

Path

Purpose

GET

/api/status

Gateway and running-task summary

GET

/api/projects

Workspace projects

GET

/api/capabilities

Registered adapters and capabilities

GET

/api/sessions

List sessions

GET

/api/tasks, /api/tasks/:id

List / inspect tasks

POST

/api/dispatch

Dispatch a task

POST

/api/tasks/:id/cancel

Cancel a task

POST

/api/evidence

Run the Evidence Gate

POST

/api/workflow

Run a generic workflow

POST

/api/review-loop

Run the compatibility review loop

POST

/api/git/commit-push

Commit and push a repository

WS

/ws?token=...

Stream task/workflow lifecycle events

Execution endpoints require an explicit cwd or project, and every resolved path must stay inside AGENT_BRIDGE_WORKSPACE.

Example generic workflow request:

{
  "project": "my-app",
  "input": "Implement the requested feature and verify it.",
  "workflow": {
    "steps": [
      {
        "type": "agent",
        "role": "implementer",
        "requires": ["fileTools", "shellTools", "sessions"],
        "prompt": "{{input}}"
      },
      {
        "type": "evidence",
        "role": "verifier",
        "testCommands": ["npm test", "npm run typecheck"]
      },
      {
        "type": "agent",
        "role": "reviewer",
        "agent": "claude",
        "prompt": "Review the implementation. Evidence: {{evidenceSummary}}\nDiff:\n{{gitDiff}}"
      }
    ]
  }
}

Evidence and review safety

Evidence verification is fail-closed. A reviewer cannot turn a failed or missing Evidence Gate into PASS merely by writing the word PASS. Review verdict parsing only accepts a verdict at the beginning of the first non-empty line.

Git commit and push results are tracked separately; a successful local commit with a failed push is reported as failure rather than success.

Security

This is a privileged local development daemon. Built-in unattended CLI adapters may disable approval/sandbox prompts so they do not hang waiting for input.

In particular:

Agent

Default unattended behavior

Codex CLI

--dangerously-bypass-approvals-and-sandbox

Antigravity

--dangerously-skip-permissions

Treat possession of the gateway token as equivalent to powerful local development access.

  • Keep the default bind address at 127.0.0.1 unless you fully trust the network.

  • Prefer the Authorization header over query-string tokens because query strings may be logged.

  • All execution paths are constrained to AGENT_BRIDGE_WORKSPACE, but agents still execute with the privileges of the OS user running Agent Bridge.

  • /api/git/commit-push pushes to the configured repository remote without a second interactive approval.

Do not expose the gateway to an untrusted network or run it under an unnecessarily privileged user.

Claude SDK status

The old ClaudeSdkAdapter used the plain Anthropic Messages API and therefore did not provide Claude Code/agent capabilities. That path has been removed. engine=sdk for Claude remains intentionally unavailable until a real Claude Agent SDK adapter is implemented.

Development and verification

npm install
npm run typecheck
npm run build
npm run test:hardening

CI runs typecheck, build, and hardening integration tests. A separate live E2E script validates real authenticated Claude/Codex/Antigravity session continuity when those CLIs are installed locally:

npm run test:agents:e2e

License

MIT

Available Tools

6 tools
agent_cancelC

Cancel a currently running agent task.

ParametersJSON Schema
NameRequiredDescriptionDefault
taskIdYesTask ID to cancel

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must disclose behavioral traits. It doesn't explain whether cancellation is immediate or graceful, if it can be undone, what happens to results, or any side effects. This is a significant gap for a cancellation operation.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, clear sentence that directly states the action. It is appropriately sized but could be slightly more informative without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's destructive nature, lack of annotations, and no output schema, the description should provide more detail on what happens after cancellation (e.g., state changes, resource cleanup, return codes). It is incomplete for a safe agent decision.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100% and the schema already describes taskId as 'Task ID to cancel'. The description adds no extra meaning beyond this, so a baseline score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb 'Cancel' and the resource 'currently running agent task', which differentiates it from siblings like agent_send or agent_status. However, it doesn't explicitly mention that the task must be running versus already completed, which is a minor gap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance is provided on when to cancel a task vs. waiting for completion, or when alternatives like agent_review_loop might be more appropriate. The description gives no context on prerequisites or consequences.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

agent_evidence_checkA

Run Evidence Gate validation: inspect git status/diff and execute test/typecheck/lint commands to produce empirical evidence report.

ParametersJSON Schema
NameRequiredDescriptionDefault
cwdNoTarget workspace directory (default: current directory)
timeoutMsNoTimeout per test command in ms (default: 60000ms)
testCommandsNoList of test commands to run (e.g. ['npm test', 'npx tsc --noEmit'])

TDQS

A3.6/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden. It explains the tool runs local commands (git, test, lint) but doesn't disclose potential side effects (e.g., modifying git state, consuming user resources, or requiring network access). The description is clear on intended behavior but lacks depth on risks or limits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that effectively conveys the tool's purpose and primary actions. It is appropriately front-loaded and contains no unnecessary words. However, given 3 parameters and no output schema, it could have included more context without being verbose.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is moderately complex (runs multiple commands, outputs a report) with no output schema. The description gives the big picture but lacks detail on what the report contains, error handling, or how timeoutMs affects operations. It's minimally complete for a 3-param tool with no output schema.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the baseline is 3. The description adds no additional parameter meaning beyond the schema; it just summarizes the tool's action. The schema already adequately describes the three parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb (Run, inspect, execute) and identifies the resource (Evidence Gate validation) with concrete actions: git status/diff and test/typecheck/lint commands. It clearly distinguishes from sibling tools which are about sending, canceling, status, sessions, and review loops.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this is used for evidence gathering before code changes, but provides no explicit guidance on when to use it vs alternatives. It doesn't mention prerequisites (e.g., the workspace having git and test commands) or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

agent_review_loopA

Execute full autonomous development loop: Codex implements -> Evidence Gate validates -> Claude reviews -> Auto-revision (up to max 2 revisions limit).

ParametersJSON Schema
NameRequiredDescriptionDefault
cwdNoTarget workspace directory (default: current directory)
topicNoTopic or feature name (e.g. 'auth-fix')
engineNoEngine to use: 'cli' (default) or 'sdk'
promptYesThe feature specification or bugfix task description
projectNoDirectory name of the project inside the workspace
timeoutMsNoTimeout per turn in ms (default: 180000ms)
maxRevisionsNoMaximum auto-revision retries (default: 2)
testCommandsNoTest commands for Evidence Gate (e.g. ['npm test'])

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries the full burden of behavioral disclosure. It clearly describes the multi-step pipeline (Codex implements -> Evidence Gate validates -> Claude reviews -> auto-revision) and the auto-revision limit of 2. This gives the agent a good understanding of what the tool does and its boundaries, though it does not discuss side effects or what gets modified.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence that front-loads the key action ('Execute full autonomous development loop') and then lists the sequential steps. Every element earns its place, no filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (8 parameters, multi-step process, no output schema), the description is reasonably complete. It explains the loop stages and constraints (max 2 revisions). However, it omits details like what 'Evidence Gate validates' entails or what the output/return value looks like, which would be helpful for an agent to determine success or failure.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so each parameter has a description in the schema. The tool description itself does not add parameter-level detail, but given full coverage, a baseline of 3 is appropriate. An extra point is earned because the description effectively frames the purpose of the 'prompt' and 'maxRevisions' parameters in the context of the loop, adding semantic meaning beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses specific verbs ('executes', 'validates', 'reviews') and clearly identifies the resource (a full development loop with multiple stages). It distinguishes itself from sibling tools like 'agent_send' or 'agent_evidence_check' by describing a multi-step autonomous process, not a single action.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context (autonomous development with revisions) and mentions a max revision limit, but does not explicitly say when to use this tool versus alternatives like 'agent_send' or 'agent_evidence_check'. There is no guidance on prerequisites or when not to use it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

agent_sendB

Send an instruction to Claude Code or Codex CLI/SDK. Executes asynchronously in background and returns task_id.

ParametersJSON Schema
NameRequiredDescriptionDefault
cwdNoWorking directory for execution (default: current directory)
agentYesTarget agent: 'claude', 'codex', or 'antigravity' (agy CLI)
modelNoSpecific model name (e.g. 'sonnet', 'opus' for Claude; 'o3' for Codex)
topicNoTopic or feature name (e.g. 'presence', 'auth')
engineNoExecution engine: 'cli' (default) or 'sdk'
promptYesInstruction or prompt text for the agent
projectNoDirectory name of the project inside the workspace
taskTypeNoRole or nature of task
sessionIdNoSpecific internal session ID to resume
timeoutMsNoExecution timeout in milliseconds (default: 180000ms / 3min)
forceNewSessionNoSet true to force create a new session instead of reusing

TDQS

B3.4/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It states that execution is asynchronous and returns a task_id, which is useful. However, it does not disclose what happens on failure, whether the task can be cancelled, rate limits, or authentication needs. The description is adequate but not comprehensive for a tool with 11 parameters.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single sentence that is concise and directly states the purpose and key behavior. It is front-loaded and efficient. However, it could include a brief example or usage note without becoming too long.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (11 parameters, 2 required, no output schema), the description is somewhat minimal. It does not explain return values (though no output schema exists), error handling, or how to poll for results (e.g., using agent_status). The description is functional but leaves gaps for an agent to fill from context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the input schema already documents all parameters. The description does not add any additional meaning beyond what the schema provides. Baseline 3 is appropriate; the description adds no value for parameter understanding.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action ('Send an instruction'), the target ('Claude Code or Codex CLI/SDK'), and the key behavior ('asynchronously in background'). It returns a task_id, which distinguishes it from synchronous tools. However, it could be slightly more specific about the 'antigravity' agent and the sibling tools, but overall it's clear and informative.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies this is for sending instructions to agents, but it does not provide guidance on when to use this tool versus alternatives like 'agent_review_loop' or 'agent_evidence_check'. No explicit when-not-to-use or alternative suggestions are given, leaving the agent to infer from sibling names.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

agent_sessionsC

List active or archived sessions tracked by Agent Bridge.

ParametersJSON Schema
NameRequiredDescriptionDefault
agentNoFilter by agent type
topicNoFilter by topic
statusNoFilter by status
projectNoFilter by project

TDQS

C2.9/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavioral traits. It only states that the tool lists sessions (a read operation), but fails to mention whether results are paginated, what permissions are needed, any rate limits, or what happens with no filters. For a listing tool with no annotation safety hints, this omission is significant.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, front-loaded sentence of six words. It is efficient and immediately communicates the tool's purpose. However, it is slightly underspecified, trading completeness for brevity. Still, it earns its place without filler.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the four optional parameters and no output schema or annotations, the description is insufficient. It does not explain how filters interact, what the response structure looks like, or how to distinguish this tool from siblings. The agent cannot fully judge when or how to invoke the tool based on this description alone.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% because all four parameters have descriptions in the JSON schema. The description adds no additional semantics beyond the schema, merely echoing the status filter. Baseline 3 is appropriate; no extra value is provided.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool lists sessions tracked by Agent Bridge, with an explicit mention of filtering by status (active/archived). However, it does not differentiate from the sibling tool agent_status, which might also provide session-level status information. The purpose is clear but lacks unique positioning relative to similar tools.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives like agent_status or agent_send. It does not mention prerequisites, exclusions, or typical use cases. The agent is left to infer usage solely from the vague action description.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

agent_statusB

Check the status, output, or error of a background task dispatched via agent_send.

ParametersJSON Schema
NameRequiredDescriptionDefault
taskIdYesTask ID returned from agent_send (e.g. 'task_claude_12345')

TDQS

B3.4/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description must fully disclose behavior. It only says 'Check,' which hints at a read-only operation, but it does not confirm idempotency, authorization requirements, or whether the tool can be called multiple times safely. The lack of behavioral details is a significant gap.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, focused sentence that immediately states the tool's purpose. No extraneous information is present, making it efficient. However, it could include brief behavioral notes without bloating the text, keeping it from a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one parameter, no output schema, no annotations), the description covers the basic purpose and parameter context. However, it lacks any indication of what the tool returns (e.g., format of status/output/error), which would help an agent invoke it correctly without relying on trial and error.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%—the taskId parameter already includes a clear description (e.g., 'Task ID returned from agent_send'). The tool description adds no new semantic value beyond what the schema provides, hitting the baseline score for high coverage without additional benefit.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description explicitly states the verb 'Check' and the resource 'status, output, or error of a background task dispatched via agent_send.' This clearly defines the tool's function and differentiates it from siblings like agent_send (dispatch), agent_cancel, and agent_evidence_check, which serve distinct roles.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage after agent_send by referencing 'task dispatched via agent_send,' but it does not explicitly state when to use this tool versus alternatives (e.g., 'use after sending a task to poll for completion'). No guidance on when not to use it is provided, leaving room for ambiguity.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

Tool Schema Changelog

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

  1. 6 tool updatesv0.2.0
    • First observedagent_cancel
    • First observedagent_evidence_check
    • First observedagent_review_loop
    • First observedagent_send
    • First observedagent_sessions
    • First observedagent_status

TDQS

A3.6/5.0

Scored across 6 tools

Disambiguation4/5

Each tool targets a distinct action: send, cancel, check evidence, check status, list sessions, and run a full review loop. The only minor overlap is between agent_send and agent_review_loop, as both can dispatch work, but the latter is a higher-level workflow clearly distinguished by name and description.

Naming Consistency5/5

All tool names consistently follow the agent_verb or agent_verb_noun pattern (e.g., agent_send, agent_evidence_check, agent_review_loop). The naming is predictable and readable across the set.

Tool Count5/5

With 6 tools, the surface is appropriately scoped for an agent orchestration and review bridge. Each tool provides a distinct function without overwhelming users or leaving the set feeling thin.

Completeness4/5

The set covers the core workflow: dispatch, status, cancel, and an integrated review loop. Evidence check and session listing add useful supporting operations. A minor gap is the lack of an explicit tool to modify or configure review loop parameters, but the overall surface is solid.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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