The MCP Census

Search MCP servers

census_search

Read-onlyIdempotent

Search MCP servers by keyword or partial name (e.g. 'github', 'postgres'). Returns ranked matches with health/trust. Also returns: resolved_query (auto typo fix), disambiguate (when unsure), known_brand (we recognize a strong product but it has no official MCP — e.g. CodeRabbit), research (watchlist/confirmed_absent), query_intent (brand_lookup|category|package|install_gate|junk — does not change ranking), intent_cta (preflight when they asked an install-gate question). Prefer official_match=true rows. Never invent servers.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "<query>"
    },
    "name": "census_search"
  }
}

Input Schema

Name	Required	Description	Default
`limit`	No	Max results 1–50 (default 20)
`query`	Yes	Keyword or partial server name (>= 2 chars). Typos and space variants are resolved when confident.

Schema Changelog

Changes observed during successful MCP inspections.

Changed2 schema fields changedSep 1, 2026

addedInput schema / properties / limit

Added value: +{
+  "description": "Max results 1–50 (default 20)",
+  "type": "number"
+}

changedInput schema / properties / query / description

Previous value: -"Keyword or partial server name (>= 2 chars)"New value: +"Keyword or partial server name (>= 2 chars). Typos and space variants are resolved when confident."

First observedJul 13, 2026

TDQS

A3.6/5.0

Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, openWorld, non-destructive), and the description goes well beyond them by disclosing ranking behavior (health/trust), auto typo resolution, and the presence of disambiguation/known_brand/research signals. The dense jargon list (query_intent, intent_cta) is disclosed but not fully explained, which keeps it short of a 5.

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

Conciseness3/5

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

The purpose sentence is front-loaded and clear, but the second half collapses seven response fields into one run-on colon list of unexplained terms. Since there is no output schema the content is warranted, yet the packing hurts readability and could be structured better.

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?

For a 2-parameter read-only search with no output schema, the description covers the essential gaps: what comes back (ranked matches with health/trust), confidence behaviors (resolved_query, disambiguate), and a failure-avoidance rule ('Never invent servers'). Slightly short of complete because the intent fields are named but not defined.

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 both query (>= 2 chars, typo/space resolution) and limit (1–50, default 20) are already documented in structured data. The description adds only the example keyword values and no additional parameter semantics such as how limit interacts with ranking, so baseline 3 applies.

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?

States a specific verb and resource ('Search MCP servers') plus the matching mode (keyword or partial name) with concrete examples, so an agent knows exactly what it retrieves. It does not explicitly contrast itself with close siblings like census_lookup, so sibling differentiation is left implicit.

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?

Usage is implied through examples ('github', 'postgres') and a result-reading rule ('Prefer official_match=true rows. Never invent servers'), which is useful. However, it never says when to use this versus census_lookup, census_preflight, or census_lookalikes, so routing is left to inference.

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

All The MCP Census tools Inspect

Try in Browser

Claude Code, inside the Godot 4 editorFlockbay puts an AI agent in the real Godot 4 editor: it writes GDScript, runs your game and fixes what breaks. Free, or bring your own Claude Code or Codex.flockbay.comAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources

Need Help?