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woodpecker-ci-mcp

woodpecker-ci-mcp

by ni-c
OverviewSchemaSourceRelated ServersDiscussionsAdmin
TypeScript
Remote

Get server version and health

get_server_info
Read-onlyIdempotent

Check Woodpecker CI server version and health without a token to confirm connectivity and isolate URL versus token problems.

Instructions

Returns the Woodpecker version and whether the server reports itself healthy. Works without a token, which makes it the call to use when nothing else does: if this answers, WOODPECKER_URL is right and the problem is WOODPECKER_TOKEN.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "get_server_info"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Output Schema

NameRequiredDescriptionDefault
noteNoPresent only when the server is Crow CI.
truncatedNoPresent only when the answer was shortened to fit the budget.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.4.0
    • addedOutput schema / properties / note
      Added value: +{
+  "description": "Present only when the server is Crow CI.",
+  "type": "string"
+}
  2. First observedv0.2.0

TDQS

A4.7/5.0
Behavior4/5

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

Annotations already establish readOnly/idempotent/non-destructive, so the bar is lower; the description still adds a real behavioral fact beyond them — it works without a token (no auth requirement), which is the whole point of the tool. It omits failure-mode specifics beyond the auth inference, but the output schema covers return shape.

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?

Two sentences, front-loaded with what it returns, then the diagnostic framing. Every clause earns its place and there is no filler.

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

Completeness5/5

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

For a 0-parameter, output-schema-backed health probe, the description supplies the one thing the structured fields cannot: the tokenless behavior and what a response implies about configuration. Nothing an agent needs to call it correctly is missing.

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?

The tool takes zero parameters, so there is nothing for the description to clarify; baseline 4 applies. Nothing in the description misleads about inputs.

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?

States a specific resource and both returned fields ('the Woodpecker version and whether the server reports itself healthy'), so an agent knows exactly what comes back. No sibling tool overlaps this read-only server-level scope.

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

Usage Guidelines5/5

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

Explicitly names the situation that selects this tool: 'the call to use when nothing else does', i.e. a connectivity/auth diagnostic. It also tells the agent how to interpret a successful answer (URL correct, token at fault), which is actionable when-to-use guidance rather than vague context.

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

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