Contentful GraphQL MCP Server

Server Quality Checklist

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Latest release: v1.2.0
Disambiguation5/5
Each tool has a clearly distinct purpose: listing content types, getting schema, getting examples, executing queries, generating a search query, and performing intelligent search. The descriptions explicitly outline the workflow, eliminating ambiguity.
Naming Consistency4/5
Most tools follow a 'graphql_' prefix with verbs like list, get, and query. However, 'build_search_query' and 'smart_search' break the pattern, introducing inconsistency despite individual clarity.
Tool Count5/5
With six tools, the set is well-scoped for a GraphQL content exploration and search server. Each tool provides core functionality without unnecessary bloat, making it easy to navigate.
Completeness4/5
The tools cover discovery, schema understanding, example learning, and query execution comprehensively. A minor gap is the lack of a direct tool for fetching a single entry by ID, but 'graphql_query' can handle it. The cached schema might not update automatically, but that's a design choice.
Average 4/5 across 6 of 6 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
- 0 commits in the last 12 weeks
- Last stable release on May 25, 2025
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI is failing
This repository is licensed under MIT License.
This repository includes a README.md file.
No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided. The description does not disclose behavior beyond executing a query. It fails to mention error handling, rate limits, whether the query is read-only, or any side effects. With no annotations, the description carries full burden but adds minimal behavioral context.
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 two sentences long, which is efficient. The first sentence is crucial usage guidance, and the second explains the benefit. A bit more detail on what the GraphQL interface offers could improve, but overall it avoids unnecessary text.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no output schema, the description should ideally hint at return structure, but it does not. The prerequisite guidance and parameter info are adequate for a query tool with 4 well-documented parameters. Missing details on response format or pagination limit completeness.
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%, and the description adds little meaningful info beyond what is in the schema. It mentions that space ID and CDA token are auto-retrieved, which is helpful context but does not deepen understanding of parameter semantics beyond schema definitions.
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?
The description clearly states the tool executes GraphQL queries against Contentful API, emphasizing flexibility. The verb 'execute' and resource 'GraphQL query' are specific. However, it could differentiate more from sibling tools like smart_search or build_search_query.
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?
The description explicitly instructs to first use graphql_list_content_types and graphql_get_content_type_schema before using this tool. This provides clear, actionable guidance on when and how to use the tool, distinguishing it from alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses key behavioral traits: it uses cached metadata and searches all text fields automatically. However, with no annotations, it lacks details on whether results are read-only, authorization requirements, rate limits, or response format. Some transparency but significant gaps remain.
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 concise sentences, front-loaded with the core action. Every sentence adds value: first defines purpose, second adds key features and benefits. No wasted words.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description provides the essential purpose and a key detail (cached metadata), but lacks information about output structure, pagination, error behavior, or limitations. For a search tool with no output schema, more contextual completeness would be expected.
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 baseline is 3. The tool description adds no extra parameter meaning beyond what the schema already provides. It mentions searching all text fields, but that is not parameter-specific.
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 performs intelligent search across multiple content types using cached metadata and automatically searches all text fields. It distinguishes from manually chaining GraphQL calls, making its purpose specific and unambiguous.
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 when cross-content-type search is needed by touting speed and ease over GraphQL chaining, but it does not explicitly state when not to use it or mention sibling alternatives like build_search_query or graphql_query. Guidance is implied rather than explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so the description bears the burden. It discloses it is a discovery tool and that credentials are auto-retrieved, but omits details like whether it mutates state or rate limits. This is minimally adequate for a read-only list operation.
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 a single, well-structured paragraph with the critical instruction front-loaded. Every sentence adds value with no repetition or fluff.
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?
The tool lacks an output schema but the core purpose is clear. It could mention the output format (e.g., list of names) but given sibling tools handle detailed schema, this is sufficient. Slight gap, but overall complete for its role.
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 has 100% coverage with descriptions for both optional parameters. The description adds only the context that these are overrides with defaults, which adds little beyond schema. Baseline 3 is appropriate.
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 that the tool lists all available content types in the Contentful GraphQL schema, using the specific verb 'lists' and resource 'content types'. It is well-differentiated from siblings like graphql_get_content_type_schema which targets a single type.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to use this tool FIRST before writing GraphQL queries, providing clear context. However, it does not mention when NOT to use it or alternatives, though siblings handle specific cases.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must cover behavioral traits. It discloses that space ID and CDA token are auto-retrieved from environment variables, indicating safe, non-destructive behavior. However, it does not describe return format or limitations, which is a gap for a tool with no output schema.
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, front-loading the critical instruction with 'IMPORTANT'. Every sentence adds value, and there is no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no output schema, the description omits details about the return format (e.g., string or object). It does state the dependency and purpose, which is adequate but not fully complete for an agent to anticipate the output.
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 input schema covers all parameters with descriptions (100% coverage). The description adds value by explaining that spaceId and environmentId have default values from environment variables, beyond what the schema says.
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's purpose: to provide example GraphQL queries for a specific content type after using another tool. The verb 'see example' and the resource 'GraphQL queries' are specific, and the sibling tools list shows distinctiveness.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly instructs to use this tool AFTER graphql_get_content_type_schema, providing clear sequential context. It does not mention when not to use or alternatives, but the sibling list offers implicit differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Discloses it is a read-only schema fetch, auto-retrieves credentials, and requires prior content type selection. Lacks explicit non-destructive statement but is implied.
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?
Three concise sentences with front-loaded 'IMPORTANT' emphasis, no unnecessary words.
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?
Complete for a simple schema-fetch tool with no output schema: covers when, why, and how to use, and what it returns.
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?
Adds value beyond schema by stating contentType is required, spaceId and environmentId are optional overrides, and includes an example. Schema coverage is 100%.
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?
Clearly states it fetches a detailed schema for a specific content type after listing types, distinguishing it from sibling tools like graphql_list_content_types and graphql_query.
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 to use after graphql_list_content_types and before creating a query, providing clear when-to-use guidance and prerequisites.
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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