chiark-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| find_agentA | Find the best AI agents for a given task. Searches 2,000+ agents across A2A and MCP ecosystems. Supports quality constraints: min uptime, max latency, min score, auth requirement, payment support. |
| check_agent_statusA | Check real-time status of an agent. Returns latest probe result: alive/dead, HTTP status, response time, TLS validity. |
| get_agent_scoreC | Get full quality score breakdown: availability (0-30), conformance (0-30), performance (0-40), uptime, latency, trend, rank. |
| report_outcomeB | Report routing outcome after using an agent. Helps improve future recommendations. Call after routing to an agent. |
| get_ecosystem_statsB | Ecosystem overview: total agents, online count, average scores, top categories, average latency. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose with no overlap: status checking, agent discovery, score retrieval, ecosystem statistics, and outcome reporting. The descriptions make it easy to differentiate between monitoring, search, analytics, and feedback functions.
All tools follow a consistent verb_noun pattern (check_agent_status, find_agent, get_agent_score, get_ecosystem_stats, report_outcome) with clear, descriptive names. The naming convention is uniform throughout the set.
With 5 tools, this server is well-scoped for agent discovery and monitoring. Each tool earns its place by covering distinct aspects of the domain: discovery, evaluation, monitoring, ecosystem overview, and feedback.
The toolset provides strong coverage for agent discovery and quality assessment, including search, scoring, status checks, and ecosystem stats. A minor gap exists in direct agent interaction or management tools (e.g., invoking agents or configuring them), but the core workflow is well-supported.