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search_servers

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Search MCP Registry for servers matching a keyword. Rank results by project tech stack relevance and evaluate GitHub maturity signals.

Instructions

Search the MCP Registry for servers matching a keyword.

Use this when the user asks for a specific server or technology. Pass project_path to automatically rank results by relevance to the project's detected tech stack — each result gets a "relevance" field ("high", "medium", "low") and a "match_reason" explaining the score.

When evaluate is True (default), each result also gets a "maturity" field with GitHub-based quality signals (stars, last commit, tier). Set evaluate=False for faster results without GitHub API calls.

After finding the right server, use configure_server with the package_identifier and registry_type from the results to install it.

Args: query: Search term (e.g. "postgres", "github", "slack", "docker"). limit: Maximum results to return (1-50, default 10). project_path: Optional project directory path. When provided, results are ranked by relevance to the detected tech stack and include credential_status for each result. evaluate: Whether to fetch GitHub maturity signals for each result (default True). Set to False for faster searches.

Returns: List of servers, each with: name, description, version, registry_type, package_identifier, transport, is_official, env_vars_required, repository_url, and source ("official" | "smithery" | "both"). When project_path is set, also includes relevance, match_reason, and credential_status. When evaluate is True, also includes maturity. All results include deterministic ranking metadata: intent_match_score, intent_match_reason, composite_score, and composite_breakdown. Smithery results also include use_count (popularity) and verified (quality badge).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes
limitNo
project_pathNo
evaluateNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

Annotations indicate readOnlyHint=true, and the description confirms it's a search operation. It adds extensive behavioral details: ranking by project_path, maturity evaluation, credential_status, and deterministic ranking metadata.

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 well-structured with clear sections (Args, Returns) and is front-loaded with the main purpose. While somewhat lengthy, every sentence adds valuable information.

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?

Given 4 parameters and an output schema, the description covers all input semantics and return fields comprehensively. It even explains conditional fields (credential_status, maturity).

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

Parameters5/5

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

Schema coverage is 0%, so the description carries full burden. It explains each parameter's purpose and effect: query (search term), limit (max results), project_path (relevance ranking), evaluate (GitHub signals).

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 clearly states it searches the MCP Registry for servers matching a keyword, with a specific verb and resource. It distinguishes itself from siblings like configure_server (install) and list_installed (view installed).

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 says 'Use this when the user asks for a specific server or technology.' It also advises when to set evaluate=False for faster searches and directs to use configure_server after finding the server.

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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