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serper-search-mcp-server

serper-search-mcp-server

by smjahid012
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
Hybrid

autocomplete

Retrieve Google Autocomplete query completions for partial search terms, optionally localized by country and language, without requiring an LLM.

Instructions

Google Autocomplete suggestions via Serper API. Returns query completions — cheap, no LLM needed.

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": "autocomplete"
  }
}

Input Schema

NameRequiredDescriptionDefault
queryYesPartial query to complete.
countryNoISO 3166-1 alpha-2 country code (e.g. "US", "GB"). Default: "US".
ui_langNoUI language (e.g. "en-US"). Default: "en".
num_resultsNoResults (1–10, default 10). Note: >10 results uses 2 Serper credits.
search_langNoLanguage code (e.g. "en", "de"). Default: "en".

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv4.0.1

TDQS

B3.4/5.0
Behavior3/5

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

With no annotations, the description carries the full burden; it does disclose the return type (query completions) and a cost trait (cheap, no LLM), which are genuinely useful. However it says nothing about rate limits, auth, or result format beyond the one-liner, leaving behavioral gaps for an unannotated tool.

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 the identity and backend, followed by the return shape and cost trait. No filler or repetition of schema content.

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 simple, single-purpose read tool with fully documented parameters and no output schema, the description covers what it does, where results come from, and its cost profile. The remaining gap is routing guidance against the search siblings rather than any missing mechanical detail.

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 query, country, ui_lang, num_results, and search_lang are all documented with examples and defaults in the schema. The description adds no parameter meaning beyond that, so the 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+resource: 'Google Autocomplete suggestions via Serper API' and clarifies the return is 'query completions' rather than search results, which implicitly separates it from the search_* siblings. It stops short of naming any sibling explicitly, so differentiation is inferential rather than stated.

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

Usage Guidelines2/5

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

There is no when-to-use or when-not-to-use guidance and no named alternative (e.g., use search for full results, autocomplete for query expansion). The 'cheap, no LLM needed' note hints at a cost rationale but does not route the agent between this tool and the many search siblings.

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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