Grokipedia MCP Server

Server Quality Checklist

Profile completionA complete profile improves this server's visibility in search results.

Latest release: v0.2.2
Disambiguation4/5
Tools are mostly distinct with clear purposes, though `get_page` overlaps functionally with `get_page_content` (preview vs full) and `get_page_citations` by including citations in its response. Descriptions clarify these distinctions, but an agent might initially hesitate between the general getter and specialized ones.
Naming Consistency4/5
Strong snake_case convention with consistent `get_page_*` pattern for article-specific operations. Minor deviations with `search` (lacks `get_` prefix) and `get_related_pages` (uses `related` instead of `page_related`), but overall readable and predictable.
Tool Count5/5
Seven tools is well-scoped for a read-only encyclopedia server. The set efficiently covers discovery (search), retrieval granularity (full page, content only, section only, sections list), verification (citations), and navigation (related pages) without bloat.
Completeness4/5
Comprehensive coverage for accessing Grokipedia articles with good traversal support (search → get → related). Minor gap: no dedicated metadata-only endpoint (though `get_page` provides it alongside preview content). No write operations, which appears intentional for this domain.
Average 4.5/5 across 7 of 7 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
- No stable releases found
- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
- CI status not available
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.
Tip: use the "Try in Browser" feature on the server page to seed initial usage.
Add a glama.json file to provide metadata about your server.
If you are the author, simply .
If the server belongs to an organization, first add glama.json to the root of your repository:
```
{
  "$schema": "https://glama.ai/mcp/schemas/server.json",
  "maintainers": [
    "your-github-username"
  ]
}
```
Then . Browse examples.
Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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

Behavior4/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Since no output schema exists, the description valuably documents the return structure ('list of citations with title, URL, and description'). The 'Tips' section adds context about grounding AI knowledge. Does not contradict annotations (readOnlyHint=true aligns with 'Get').
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?
Excellent structure with clear section headers ('Use for:', 'Returns:', 'Tips:'). Information is front-loaded with the core purpose, and every sentence provides distinct value (use cases, return format, usage tips) without redundancy.
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?
For a simple 2-parameter read-only tool, the description is complete. It compensates for the missing output schema by detailing the return format, leverages annotations for safety profile, and provides sufficient context for an agent to invoke correctly.
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%, with slug and limit fully documented in the schema. The description does not add parameter-specific guidance, which is acceptable given the schema completeness—baseline score applies.
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?
Description opens with specific verb ('Get') and resource ('source citations for a Grokipedia article'), clearly distinguishing this from siblings like get_page or get_page_content which retrieve article content rather than bibliographic sources.
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?
Provides explicit 'Use for' section listing specific scenarios (verifying claims, academic research, fact-checking), offering strong positive guidance. Lacks explicit 'when not to use' or named sibling alternatives, though the specific use cases effectively imply the boundaries.
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?
Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds valuable behavioral context: it discloses the return format ('list of related pages with titles and slugs') and workflow integration ('Use returned slugs with get_page'), which is crucial given no output schema exists.
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?
Description uses clear structural headers ('Use for:', 'Returns:', 'Tips:') that front-load critical information. Every sentence earns its place — main purpose, use cases, return values, and workflow tips — with zero redundancy or filler.
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?
Given the lack of an output schema, the description adequately explains return values ('list of related pages with titles and slugs'). It also covers workflow integration with sibling tools (get_page). For a 2-parameter read-only tool with complete schema coverage, this description provides sufficient context for correct invocation.
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%, with both 'slug' and 'limit' fully documented in the schema. The description mentions 'slugs' in the Tips section reinforcing the parameter concept, but does not add semantic meaning or format details beyond what the schema already provides. Baseline 3 is appropriate when schema carries the burden.
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 'Discover[s] related Grokipedia pages linked from an article' — providing a specific verb (discover), resource (related pages), and scope (linked from an article). This effectively distinguishes it from siblings like get_page (content retrieval) and search (full-text search).
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 'Use for:' section explicitly lists scenarios: 'exploring connected topics, building knowledge graphs, follow-up research.' The 'Tips:' section mentions using returned slugs with get_page, providing workflow guidance that implicitly distinguishes this tool's output from get_page's full content retrieval. Lacks explicit 'when not to use' exclusions.
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?
While annotations confirm read-only/idempotent status, the description adds crucial behavioral context: it discloses the return structure (title, full content, content_length), format (raw markdown), and operational tip about adjusting max_length for long articles—essential given the lack of an 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?
Uses an efficient structured format (main description, Use for, Returns, Tips) with zero filler. Every sentence conveys distinct information about scope, usage, output, or configuration.
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?
Given the lack of output schema, the description comprehensively documents return values and format. Combined with complete schema coverage and clear sibling differentiation, it provides sufficient context for an agent to invoke the tool correctly.
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?
With 100% schema coverage establishing a baseline of 3, the description adds meaningful usage semantics for max_length by advising to 'set max_length higher for very long articles' and explaining its effect on returned content ('up to max_length').
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 opens with a specific verb-resource combination ('Get full article content from Grokipedia') and immediately distinguishes itself from the sibling tool get_page by noting it returns 'larger than get_page preview,' clearly establishing its scope relative to alternatives.
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?
Provides explicit 'Use for' section listing specific scenarios (reading complete articles, comprehensive research). Implicitly contrasts with get_page via size comparison, though it stops short of explicitly stating 'use get_page instead for previews.'
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?
Annotations already cover safety profile (readOnly, idempotent, non-destructive). The description adds valuable behavioral context by describing the return value structure ('list of sections with level (1=H1, 2=H2, etc.) and header text') which compensates for the missing 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?
Excellent structure with clear semantic sections ('Use for:', 'Returns:', 'Tips:'). Information is front-loaded with the core purpose in the first sentence. No redundant or wasteful text; every line provides actionable guidance.
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?
For a simple single-parameter tool with complete schema coverage and safety annotations, the description is comprehensive. It explains the output format (despite no output schema), clarifies relationships to sibling tools, and provides workflow guidance. No significant gaps remain.
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% description coverage for the 'slug' parameter ('Unique slug identifier of page to list sections for'). The description does not add additional parameter semantics, meeting the baseline expectation when schema documentation is complete.
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?
Description opens with specific verb 'Get' and clear resource 'table of contents (all section headers) for a Grokipedia article'. It effectively distinguishes from siblings like get_page_content (full text) and get_page_section (single section) by emphasizing it retrieves ALL headers/structure.
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?
Provides explicit 'Use for:' scenarios (understanding structure, finding sections) and critically includes 'Tips: Call before get_page_section to find valid section headers' - directly naming a sibling tool and establishing the correct workflow sequence.
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?
Annotations already declare read-only, idempotent, non-destructive traits. The description adds valuable behavioral context by documenting return fields ('title, slug, snippet, relevance score, view count') and data relationships (slug is specifically 'for get_page'), compensating for the missing 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?
Excellent structure with clear visual scanning cues ('Use for:', 'Returns:', 'Tips:'). Every sentence earns its place—no redundancy with structured fields. Front-loaded with the core action.
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?
Comprehensive given the tool complexity. Despite no output schema, the description documents return values. Combined with 100% input schema coverage and strong annotations, the description provides sufficient context for correct invocation and result handling.
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?
With 100% schema description coverage, the baseline is appropriately 3. The description does not add parameter-specific semantics beyond what's in the schema (e.g., no syntax examples or query formatting tips), but references 'relevance' and 'view count' which map to sort_by options.
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 opens with a specific verb ('Search') and clear resource ('Grokipedia'), distinguishing it from sibling 'get_page' tools that retrieve specific content. The parenthetical '(AI-curated knowledge base)' adds essential context about the data source.
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 lists use cases ('finding Grok-generated articles, discovering AI-synthesized knowledge, research') and provides a specific workflow tip linking to siblings ('Use the slug from results with get_page/get_page_content'). This clearly establishes when to use search vs. retrieval tools.
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?
Annotations declare readOnly/idempotent/non-destructive properties. Description adds valuable behavioral context: return format ('section header and content') and operational workflow (discovery prerequisite). No contradictions with annotations; 'Extract' aligns with readOnlyHint=true.
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?
Extremely efficient structure using labeled clauses (Use for:, Returns:, Tips:). Every sentence earns its place—no filler. Front-loaded with core purpose, followed by usage context and workflow tip. Optimal length for quick agent comprehension.
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?
No output schema exists, but description compensates by stating return format ('section header and content'). Workflow guidance (use get_page_sections first) provides necessary operational context. Lacks error handling documentation (e.g., section not found), but adequately complete given schema richness.
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?
Schema coverage is 100% with complete property descriptions. Description enhances semantics by providing concrete example values for section_header ('History', 'Applications') that clarify expected input format beyond the schema's generic 'Exact header text' description.
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?
Description states specific action ('Extract') + resource ('section from a Grokipedia article') + mechanism ('by header name'). It clearly distinguishes from sibling 'get_page_sections' by targeting a specific section rather than listing all sections.
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 states when to use ('focusing on particular aspects of a topic') and provides concrete examples ('History', 'Applications'). Critically, it names the sibling alternative 'get_page_sections' with specific instruction to use it first, establishing clear workflow precedence.
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?
Annotations declare readOnly/idempotent/destructive profile. Description adds crucial behavioral context: content is 'truncated' (distinguishing from full content sibling) and specifies exact return fields (title, description, citations list). Could enhance with rate limit or caching notes, but adequately supplements annotations.
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?
Efficiently structured with clear sections (implied purpose, Use for, Returns, Tips). Zero redundancy; every line provides actionable guidance. Front-loads core purpose in first sentence.
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?
For a 2-parameter read operation without output schema, description comprehensively documents return structure and differentiates from 5 sibling tools. No gaps given tool complexity.
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?
Schema has 100% coverage documenting both slug and max_content_length. Description adds semantic value by specifying 'Slug comes from search results'—guidance not present in schema about parameter provenance—exceeding baseline expectations for high-coverage schemas.
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?
Opens with specific verb+resource ('Get complete Grokipedia page') and explicitly scopes the operation to 'metadata, content preview, and citations'. Clearly distinguishes from sibling get_page_content by noting this returns truncated preview content.
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?
Provides explicit 'Use for' section listing appropriate contexts (reading articles, overviews, checking citations). Names specific alternative 'Use get_page_content for full untruncated content' and notes prerequisite 'Slug comes from search results'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

Confirm that the MCP server is working as expected.
Confirm that there are no obvious security issues.
Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

Copy to your README.md:

[![mcp-grokipedia-tool MCP server](https://glama.ai/mcp/servers/TheOneTrueNiz/mcp-grokipedia-tool/badges/card.svg)](https://glama.ai/mcp/servers/TheOneTrueNiz/mcp-grokipedia-tool)

Score Badge

Copy to your README.md:

[![mcp-grokipedia-tool MCP server](https://glama.ai/mcp/servers/TheOneTrueNiz/mcp-grokipedia-tool/badges/score.svg)](https://glama.ai/mcp/servers/TheOneTrueNiz/mcp-grokipedia-tool)

Latest Blog Posts

Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)
By Om-Shree-0709 on July 25, 2026.
mcp
Agent Identity
OAuth 2.1
Your AI Chatbot Just Exposed Your CEO's Salary to an Intern
By Om-Shree-0709 on July 2, 2026.
Agent Identity
MCP Security
OAuth Delegation
Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)
By Om-Shree-0709 on June 30, 2026.
Agentic Ai
Prompt Injection
WebAssembly

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/TheOneTrueNiz/mcp-grokipedia-tool'

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