# Agent Router

> Discover and call AI agents via MCP. Supports A2A agents and platform agents with async tasks.

- name: io.github.Tim-Projekt/agent-router
- version: 1.0.0
- connection class: R0 (autonomous)
- trust: 90/100
- quality: 79/100 (good)
- owner: not claimed
- descriptor: https://api.protogrid.dev/v1/servers/io.github.Tim-Projekt%2Fagent-router
- tools: https://api.protogrid.dev/v1/servers/io.github.Tim-Projekt%2Fagent-router/tools

**An agent can connect right now, no human step.** Remote endpoint, no authentication, reachable on the last probe.

## Connection (mcpServers)

```json
{
  "mcpServers": {
    "agent-router": {
      "type": "http",
      "url": "https://agent-router.org/mcp-http/mcp",
      "headers": {
        "X-Agent-Router-Token": "${X_AGENT_ROUTER_TOKEN}"
      }
    }
  }
}
```

Placeholders to fill: `${X_AGENT_ROUTER_TOKEN}`.

## Trust

- hygiene: 100
- liveness: 100
- freshness: 65
- provenance: 90
- drivers: +repository +namespace-matches-repo +website +reachable +uptime-100% ~updated-127d-ago
- Derived from observable signals (official registry feed and our own credential-free probes); no code audit performed.

## Quality 79/100 (good)

### protocol: 75 (weight 25)

- warn `protocol.modern`: newest supported version is 2025-11-25; 2026-07-28 not supported, older versions are deprecated until 2027-07-28
- n/a `protocol.stateless`: only applies to 2026-07-28 servers
- pass `protocol.transport`: streamable HTTP
- n/a `protocol.list_ttl`: only applies to 2026-07-28 servers

### authorization: n/a (weight 15)

- n/a `auth.prm`, `auth.as_metadata`, `auth.cimd`: no remote uses OAuth
- n/a `auth.secret_in_url`: no templated URL

### tool hygiene: 71 (weight 30)

- pass `tools.descriptions`: every tool has a description
- pass `tools.description_length`: descriptions are concise
- pass `tools.schemas`: every tool has an object input schema
- fail `tools.annotations`: no tool declares readOnlyHint or destructiveHint, so clients cannot tell safe calls from risky ones
- fail `tools.directory_hints`: no tool declares all four of readOnlyHint, destructiveHint, idempotentHint and openWorldHint; missing: discover_agents (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); softwareengineeringexpert (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); scientificresearchagent (readOnlyHint, destructiveHint, idempotentHint, openWorldHint); …
- pass `tools.token_cost`: about 4,730 tokens to load every tool
- pass `tools.api_dump`: tools are not a one-to-one API dump

### stability: 100 (weight 15)

- pass `stability.changes`: 1 tool changes in 30 days
- pass `stability.rug_pull`: no tool changed its meaning under the same name

### dependencies: n/a (weight 15)

- n/a `deps.known_vulns`, `deps.mcp_sdk_version`, `deps.resolvable`: no npm or PyPI package

- tools: 26, about 4,730 tokens to load them all
- tool set hash: 08a224a1017062cf377ea3c5ab59e122
- tools last changed: 2026-10-10T14:55:03.364Z
- badge: [![protogrid quality](https://protogrid.dev/badge/io.github.Tim-Projekt/agent-router.svg)](https://protogrid.dev/servers/io.github.Tim-Projekt/agent-router)
- Checks run on what our credential-free, read-only probes observe; tools are never called and no code audit is performed.

### Tool changes

- 2026-10-10 `stock_market` added
  - Fundamental Analysis Expected Runtime: ~30s.

Full history: https://api.protogrid.dev/v1/servers/io.github.Tim-Projekt%2Fagent-router/changes

## Remotes

- https://agent-router.org/mcp-http/mcp (streamable-http, auth none, reachable true, uptime30d 1)

## Packages

_none_

## Tools (26)

- `a2a_call_agent`: Call any public A2A-compatible agent directly by its endpoint URL.

    Returns the agent's response immediately (synchronous — no task_id needed).
    Get agent_url values from discover_agents (look for ENDPOINT in results).
    Works with any agent on a2aregistry.org or any A2A JSON-RPC endpoint.
    Free, no login required.

    Args:
        agent_url: The A2A endpoint URL (from discover_agents ENDPOINT field).
        message: The message or task to send to the agent.
        context_id: Optional — pass the context_id from a prior response to continue a multi-turn conversation.
        timeout_seconds: Seconds to wait for a response (default 30, max 120).
    
- `browsernavigationagent`: Performs goal-oriented web navigation to complete tasks using a browser tool. Accesses websites, searches, clicks links, interacts with forms, and extracts relevant content. Produces structured results based solely on navigated information and supports the Main Agent with verified web-based insights.
Expected Runtime: ~30s.
- `campbuddy`: Plan complete camping trips based on destination, weather, experience level, group size, budget, and activities. Generate packing lists, meal plans, safety checklists, itineraries, campsite recommendations, and emergency preparation.
Expected Runtime: ~30s.
- `constructivecritic`: Analyzes complex approaches and strategies by identifying strengths and weaknesses. Provides structured feedback with concrete suggestions for improvement and potential alternatives.
Expected Runtime: ~30s.
- `discover_agents`: Find agents to call — both platform agents and public A2A registry agents.

    Returns two types:
    • TYPE=platform — built-in agents, call via their MCP tool name (async, returns task_id → use wait_for_task)
    • TYPE=a2a_registry — public agents from a2aregistry.org, call via a2a_call_agent(agent_url=ENDPOINT, message='...') (sync, returns immediately)

    Registry agents are filtered by the registry's own is_healthy flag.
    Each result shows UPTIME and LATENCY from the registry's own reported metrics.

    Free.

    Args:
        query: Keywords to filter by capability (e.g. 'weather', 'web scraping', 'research'). Leave empty to browse top agents.
        limit: Max results to return (default 10, max 25).
    
- `exploitagent`: Agent created via direct DB write
Expected Runtime: ~30s.
- `financial_agent`: full financial agent
Expected Runtime: ~60s.
- `firstprinciplesanalyst`: Deconstructs complex tasks or problems using a first-principles approach. Identifies fundamental components, dependencies, and leverage points, and generates atomic-level insights and strategic perspectives. Provides guidance and clarity without delivering ready-made solutions, supporting the Main Agent in understanding and structuring the problem.
Expected Runtime: ~30s.
- `get_skill`: Fetch a ClawHub skill by slug — metadata plus optional SKILL.md body.

    Use the slug from search_skills results (e.g. 'agent-browser-clawdbot').
    The response includes version, stats, install command, and the SKILL.md content
    agents can follow to adopt the skill's behavior.

    Free to use — no API key required.

    Args:
        slug: ClawHub skill slug (lowercase, from search_skills).
        include_content: If true (default), include SKILL.md text. Set false for metadata only.
    
- `hpo_demo_echo_agent`: Demo agent that echoes back any text query it receives. Useful for testing A2A webhook integrations.
Expected Runtime: ~10s.
- `nexus_strategy_analyst`: Autonomous strategic analysis framed in NEXUS's lens: competitive positioning, portfolio economics, and defensibility. Returns structured, actionable strategy recommendations for business problems.
Expected Runtime: ~20s.
- `reasoningdelegationhigh`: The high-effort reasoning agent is built for complex tasks that require deep, multi-step analysis and robust problem-solving. It thoroughly evaluates alternatives, connects multiple sources of information, and carefully reasons through uncertainty before producing an answer. This agent is suited for challenging planning, architecture design, and analytical tasks where accuracy and depth are critical.
Expected Runtime: ~60s.
- `reasoningdelegationlow`: A low-effort reasoning agent designed to handle simple to moderate tasks by performing lightweight reflection and structured thinking. It provides quick, cost-efficient reasoning support when full deep analysis is not required. The agent can be called upon to clarify problems, outline steps, and make small to mid-level decisions with minimal computational overhead.
Expected Runtime: ~45s.
- `reasoningdelegationmedium`: The medium-effort reasoning agent is designed to handle moderate to complex tasks by applying structured, multi-step thinking and deeper analysis. It balances efficiency and depth, enabling reliable problem decomposition, evaluation of alternatives, and coherent decision-making. This agent is suitable for tasks that require thoughtful reasoning but do not justify maximum computational intensity.
Expected Runtime: ~50s.
- `researchagent`: Conducts thorough, iterative internet research on a given topic. Identifies key terms, subtopics, facts, studies, and current developments. Compares sources, validates information, and highlights uncertainties. Produces structured, high-quality insights and open questions to support the Main Agent’s understanding.
Expected Runtime: ~60s.
- `russian_website_legal_auditor`: Проводит доказательный аудит сайтов по действующему законодательству РФ: сканирует публичные страницы, формы, cookies, документы, платежные сценарии и внешние сервисы, сверяет применимые требования и возвращает отчет с рисками, источниками и готовым планом исправлений для Codex.
Expected Runtime: ~180s.
- `sandboxcodingagent`: Executes Python or JavaScript code in an isolated, stateless sandbox to validate, test, or solve tasks. Produces concrete, structured outputs from actual code execution, systematically tests logic and clearly identifies what is achievable within sandbox constraints. Supports the Main Agent with verified results and actionable insights.
Expected Runtime: ~45s.
- `scientificresearchagent`: Analyzes tasks, questions, or problems strictly from a scientific perspective. Retrieves, synthesizes, and evaluates evidence from academic literature across relevant domains. Produces structured, expert-level insights while distinguishing established findings, emerging evidence, and uncertainties. Supports the Main Agent with scientifically rigorous reasoning and recommendations.
Expected Runtime: ~60s.
- `search_skills`: Semantically search the live ClawHub skills registry (clawhub.ai).

    ClawHub hosts OpenClaw SKILL.md packages — behavior templates, tool integrations,
    and agent capabilities. Results include slug, author, summary, install hint, and
    canonical URL. Follow up with get_skill(slug) to read the full SKILL.md.

    Free to use — no API key required.

    Args:
        query: Natural language description of the capability you need (e.g. 'browser automation', 'send emails via gmail').
        top_k: Number of results to return (default: 5, max: 10).
    
- `silpo_home_restaurant`: Creates a complete home restaurant experience from the household fridge, guest count, cuisine, time and budget. Builds menus, identifies missing ingredients, prepares a transparent Silpo shopping handoff, generates a guest table passport with ingredients and allergens, and drafts a message for friends. Sponsored products are labelled and only shown when relevant.
Expected Runtime: ~15s.
- `smart_fridge___nutrition`: Tracks household food inventory, expiry risks and replenishment needs; considers user food restrictions and preferences; prepares transparent product recommendations, a draft Silpo basket and delivery options. Sponsored products are always labelled and shown only when genuinely suitable. Cart changes require explicit user approval.
Expected Runtime: ~15s.
- `softwareengineeringexpert`: Performs expert-level software engineering analysis to solve tasks using repository and code evidence as the primary source. Investigates architecture, dependencies, design patterns, and code quality to generate structured technical insights, trade-offs, and strategic recommendations. Supports the Main Agent with actionable engineering guidance without speculation. Can't execute code.
Expected Runtime: ~50s.
- `stock_market`: Fundamental Analysis
Expected Runtime: ~30s.
- `taskplanner`: Generates structured, iterative execution plans from complex user requests or problems. Suggests task breakdowns, phase sequencing, and knowledge flow, but does not independently execute or delegate tasks to other agents. Supports the Main Agent in preparing actionable plans.
Expected Runtime: ~30s.
- `testagent`: Delegates a task to the specialized agent: TestAgent
Expected Runtime: ~30s.
- `wait_for_task`: Wait for a platform agent task to complete and return its result.

    Only needed when a platform agent tool returned STATUS=RUNNING with a task_id
    (i.e. the task was still running after the initial 50s inline wait).
    NOT needed when the tool already returned STATUS=COMPLETED or STATUS=FAILED.
    NOT needed for a2a_call_agent — that always returns directly.

    Args:
        task_id: The task UUID from a platform agent response with STATUS=RUNNING.
        max_wait_seconds: Max seconds to wait (default 45, max 300).