GraphOS MCP Tools
Server Details
Search Apollo docs, specs, and best practices
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- apollographql/apollo-mcp-server
- GitHub Stars
- 295
- Server Listing
- Apollo MCP Server
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Tool Definition Quality
Average 4.6/5 across 3 of 3 tools scored.
Each tool serves a distinct purpose: providing the connectors specification, searching documentation, and reading full documentation pages. There is no overlap or ambiguity.
All tools follow a consistent ApolloDocs prefix and CamelCase naming pattern (ApolloConnectorsSpec, ApolloDocsRead, ApolloDocsSearch), with each name clearly indicating the action (Spec, Read, Search).
Three tools is appropriate for a focused documentation server. This number is well within the typical 3-15 range and covers the core needs of spec guidance, search, and full page retrieval.
The tool set covers the essential operations for interacting with Apollo documentation: searching, reading full pages, and accessing the connectors specification. There are no obvious missing operations for this domain.
Available Tools
3 toolsApolloConnectorsSpecARead-onlyIdempotentInspect
This tool provides the agent with the specification which describes how to use Apollo Connectors in a graphql schema to send an HTTP request or use any REST API with a graph. A user may refer to an Apollo Connector as 'Apollo Connector', 'REST Connector', or even just 'Connector'. Treat these all as synonyms for the same thing. You MUST ALWAYS call this tool to use this specification as a guide BEFORE planning, making, or proposing ANY edits or additions to a connectors schema file and/or a graphql file containing @connect or @source. This tool is to provide the agent with guidance, not the user.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate read-only, idempotent, non-destructive behavior. Description adds value by specifying that the tool provides guidance to the agent (not user) and clarifying synonyms.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences: purpose, synonym clarification, usage mandate. No wasted words, key info front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Tool is simple with no params, rich annotations, and description covers all necessary context: what it provides, synonyms, mandatory usage. No gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
No parameters exist, so schema coverage is 100%. Description needs no parameter details; baseline 4 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states it provides the specification for using Apollo Connectors, defines synonyms, and distinguishes from sibling tools (ApolloDocsRead/Search) by its specific mandate.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states 'MUST ALWAYS call this tool...BEFORE planning, making, or proposing ANY edits', giving clear when and necessary conditions.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ApolloDocsReadARead-onlyIdempotentInspect
Fetches the complete markdown content of an Apollo documentation page using its slug, or everything after https://apollographql.com/docs. Documentation slugs can be obtained from the SearchDocs tool results. Use this after ApolloDocsSearch to read full pages rather than just excerpts. Content will be given in chunks with the totalCount field specifying the total number of chunks. Start with a chunkIndex of 0 and fetch each chunk.
| Name | Required | Description | Default |
|---|---|---|---|
| slug | Yes | The slug returned from the ApolloDocsSearch tool | |
| chunkIndex | Yes | The character index to start reading from, will return up to the next 10000 characters |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide safety cues (read-only, idempotent). Description adds chunking behavior: content is chunked with totalCount field, instructing to start at chunkIndex 0 and fetch sequentially. This adds transparency beyond annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Three sentences, no fluff. Purpose, source of input, and usage pattern are front-loaded. Every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (2 params, read-only, no output schema but described chunking), the description is complete. It explains how to fetch full pages after search, handle chunking, and uses annotations to reinforce safety.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100%, but description adds meaningful usage context: slug comes from SearchDocs, chunkIndex acts as character offset returning up to 10000 characters, and hints to iterate chunks. This provides practical guidance beyond schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool fetches complete markdown content of an Apollo documentation page using a slug, and differentiates from the sibling ApolloDocsSearch by indicating it is used for reading full pages after searching.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly states to use after ApolloDocsSearch to read full pages rather than excerpts, and mentions slugs are obtained from SearchDocs results. Provides clear when-to-use guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
ApolloDocsSearchARead-onlyIdempotentInspect
Searches official Apollo GraphQL documentation (Apollo GraphQL, GraphOS, Apollo Router, Apollo Client, API orchestration, MCP Server, schema design, deployment best practices, connectors, and platform usage). Returns url, slug, and markdown content excerpts. For complete page content, you MUST use the returned slug with the ApolloDocsRead tool. Use this tool when you need technical information, configuration examples, best practices, and troubleshooting guides for any Apollo GraphQL technology.
Use the ApolloDocsRead tool to get all of the content for a given search result using the slug, don't use a WebSearch.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Use terms that would lead to broad result with a maximum of 2 keywords. |
Tool Definition Quality
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate readOnlyHint=true, destructiveHint=false, idempotentHint=true. Description adds that it returns url, slug, and markdown content excerpts, and instructs to use ApolloDocsRead for full content. Does not contradict annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured and efficient, but slightly verbose with repeated references to Apollo GraphQL. Still, every sentence adds value and the purpose and usage are front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool is a search tool with one required parameter, the description covers all essential aspects: what is searched, output format, and how to proceed with results. No output schema exists, so the description adequately describes return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The one parameter 'query' is described in schema with good guidance (broad result, max 2 keywords). The description does not add additional parameter semantics beyond what the schema provides. Since schema coverage is 100%, baseline is 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool searches official Apollo GraphQL documentation, listing specific document types. It distinguishes from sibling ApolloDocsRead by indicating that ApolloDocsSearch is for searching and returning excerpts, while ApolloDocsRead is for full content.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Explicitly specifies when to use this tool (for technical information, configuration examples, etc.) and when not (don't use WebSearch, use ApolloDocsRead for full content using the returned slug). Provides clear alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
Discussions
No comments yet. Be the first to start the discussion!
Your Connectors
Sign in to create a connector for this server.