Skip to main content
Glama
ivo-toby

Contentful GraphQL MCP Server

build_search_query

Generate a GraphQL search query for a specific content type, returning the query string and variables needed to search text fields.

Instructions

Generate a GraphQL search query for a specific content type based on cached schema information. Returns the query string and variables needed to search text fields in the content type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
contentTypeYesThe content type to build a search query for
searchTermYesThe term to search for
fieldsNoOptional: Specific fields to search (default: all searchable text fields)
spaceIdNoOptional override for the space ID (defaults to SPACE_ID environment variable)
environmentIdNoOptional override for the environment ID (defaults to ENVIRONMENT_ID environment variable or 'master')
Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses the return type (query string and variables) and mentions reliance on cached schema. However, it does not discuss side effects (none expected), required permissions, or error conditions (e.g., missing schema). This is adequate but not fully transparent.

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?

The description is two sentences with no extraneous words. It front-loads the core purpose and output, achieving high conciseness.

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?

Given the tool has 5 parameters with complete schema descriptions and no output schema, the description adequately explains the tool's role and output. It could be improved by linking to the graphql_query sibling or clarifying default field behavior, but it is mostly complete.

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?

Input schema coverage is 100%, so the description adds minimal value beyond the schema. It mentions 'search text fields' but does not elaborate on how searchTerm is processed (e.g., partial match, case sensitivity). The description does not compensate for missing schema documentation because none is missing.

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 the tool generates a GraphQL search query for a specific content type, using cached schema, and returns the query string and variables. This is a specific verb+resource combination that differentiates it from sibling tools like graphql_query (which executes queries) and smart_search.

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?

The description implies usage (to build a search query) but does not explicitly state when to use this tool versus alternatives, such as using graphql_query for execution or smart_search for more advanced search. No exclusion criteria are provided.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ivo-toby/contentful-mcp-graphql'

If you have feedback or need assistance with the MCP directory API, please join our Discord server