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CSOAI-ORG

Keyword Extractor AI MCP

by CSOAI-ORG
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Python

MCP Scorecard: 86/100

Keyword Extractor Ai MCP

MEOK AI Labs EU AI Act License PyPI

Keyword extraction MCP — TF-IDF, RAKE, YAKE, semantic relevance, search volume estimation

Keyword extraction MCP — TF-IDF, RAKE, YAKE, semantic relevance, search volume estimation. MIT.

🚀 Quick Start

# Install via pip
pip install keyword_extractor_ai_mcp

# Or install via Smithery
npx -y @smithery/cli@latest install keyword-extractor-ai-mcp --client claude

Related MCP server: Feedback Analyzer AI MCP

✨ Features

  • MCP protocol compliant

  • Easy installation

  • Well-documented API

  • Production-ready

  • Active maintenance

📖 Documentation

🛡️ Compliance

This MCP server is built with EU AI Act compliance built-in:

  • ✅ Article 9 — Risk Management System

  • ✅ Article 13 — Transparency & Instructions for Use

  • ✅ Article 15 — Bias Detection & Testing

  • ✅ Article 26 — FRIA Support (where applicable)

  • ✅ Article 50 — AI Content Watermarking (where applicable)

Need help getting compliant? Book a free 15-min diagnostic →

🏢 Enterprise

Need custom development, SLA guarantees, or white-label deployment?

  • Pro: $99/mo — Full MCP suite + EU AI Act tracking

  • Enterprise: $499/mo — Custom dev + SLA + Dedicated support

View Pricing → | Contact Sales →

🤝 Part of the MEOK Ecosystem

This server is part of the MEOK AI Labs ecosystem — 300+ MCP servers for sovereign AI governance.

Domain

Purpose

councilof.ai

EU AI Act compliance marketplace

safetyof.ai

AI safety & monitoring

meok.ai

Sovereign AI platform

cobolbridge.ai

Legacy modernization

📜 License

MIT © CSOAI-ORG

Pairs with MEOK Governance Suite

Build something that touches users? You need compliance. MEOK ships 38 governance MCPs that drop in alongside this tool — EU AI Act, DORA, NIS2, CRA, GDPR, ISO 42001, FDA SaMD, MDR, Basel, MiFID II, MiCA, COPPA, and more.

# One-shot install of the governance pack
npx meok-setup --pack governance

Free tier: 10 calls/day per MCP. Pro tier (£79/mo): unlimited + cryptographically signed compliance attestations your auditor verifies independently.

→ Full catalogue: councilof.ai/catalogue → MEOK AI Labs: meok.ai

💸 Try MEOK in 30 seconds — instant buy ladder

Tier

Price

What you get

Stripe

Smoke test

£1

Signed sample MCP-Hardening report + Article 50 PDF

https://buy.stripe.com/aFa7sNcgAdQS0ZT1Uc8k91t

Quick Kit

£9

EU AI Act Article 50 implementation guide (C2PA + EU-Icon)

https://buy.stripe.com/aFa7sNcgAdQS0ZT1Uc8k91t

Founder Call

£29

30-min 1-on-1 with the founder

https://buy.stripe.com/aFa7sNcgAdQS0ZT1Uc8k91t

Refundable. UK Stripe — VAT-clean. Builds on the 81-MCP MEOK fleet. Verify any signed report at https://meok.ai/verify.

Configuration

Add to your claude_desktop_config.json (Claude Desktop) or your MCP client config:

{
  "mcpServers": {
    "keyword-extractor-ai-mcp": {
      "command": "uvx",
      "args": ["keyword-extractor-ai-mcp"]
    }
  }
}

Or: pip install keyword-extractor-ai-mcp then run the keyword-extractor-ai-mcp command (stdio transport).

Examples

Once configured, ask your assistant, for example:

  • "Use extract_keywords to …"

  • "Use analyze_density to …"

  • "Use suggest_tags to …"

Available Tools

4 tools
analyze_densityA

Calculate keyword density for SEO analysis, with target keyword tracking and recommendations.

Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: text (str): The text to analyze or process. target_keywords (str): The target keywords to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYes
api_keyNo
target_keywordsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.1/5.0
Behavior5/5

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

A dedicated 'Behavioral Transparency' section covers side effects (read-only), authentication, rate limits, error handling, idempotency, and data privacy comprehensively. Since no annotations are provided, the description fully carries the burden, and it does so excellently.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections but is verbose, repeating some behavioral info (e.g., read-only appears in both the initial behavior note and the transparency section). Some sentences could be trimmed without losing meaning.

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 description covers purpose, usage, behavior, and transparency thoroughly. It assumes an output schema exists (which it does), so omission of return value details is acceptable. Minor gaps: no explanation of how to include keywords (e.g., comma-separated) or what the recommendations format looks like.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description lists the three parameters but adds minimal meaning: e.g., 'text (str): The text to analyze or process' merely repeats the name and type. With 0% schema description coverage, the description fails to compensate by explaining formats or relationships, leaving agent confusion about how to specify target_keywords or api_key.

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 calculates keyword density for SEO analysis with target keyword tracking and recommendations. This specific verb+resource combination distinguishes it from siblings like compare_keywords, extract_keywords, and suggest_tags.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing context for structured analysis and caution against real-time decision-making without human review. However, it does not directly compare with sibling tools.

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

compare_keywordsA

Compare keywords between two texts to find common, unique, and differentiating terms.

Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: text_a (str): The text a to analyze or process. text_b (str): The text b to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

ParametersJSON Schema
NameRequiredDescriptionDefault
text_aYes
text_bYes
api_keyNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.1/5.0
Behavior5/5

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

A dedicated 'Behavioral Transparency' section details side effects (none), authentication (none for basic), rate limits (10/day free), error handling (structured errors), idempotency (fully), and data privacy (no storage). This goes well beyond what annotations would provide, fully informing an AI agent of all behavioral traits.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-organized into sections but contains redundancy: the 'Behavior:' section and 'Behavioral Transparency' section overlap significantly, repeating similar information. It could be more concise by merging these sections.

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's complexity (comparing keywords, multiple parameters, output schema), the description covers most relevant aspects: behavior, usage guidance, error handling, and rate limits. However, it lacks explanation of the output format or examples, which would be helpful for an agent to properly interpret results.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema coverage, the description must compensate but fails: it merely repeats parameter names with trivial descriptions like 'The text a to analyze or process.' No additional semantics, constraints, examples, or formatting details are provided for any of the three parameters.

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 first sentence clearly states the tool's purpose: 'Compare keywords between two texts to find common, unique, and differentiating terms.' This is a specific verb and resource, and it differentiates from siblings like 'extract_keywords' or 'suggest_tags' which focus on extraction or suggestion rather than comparison.

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 includes explicit 'When to use' and 'When NOT to use' sections, advising for structured analysis and against use in real-time production without review. However, it does not mention specific alternatives among siblings, and the guidance is somewhat generic, lacking concrete scenarios where this tool is preferred.

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

extract_keywordsA

Extract top keywords using TF-IDF scoring with stop word filtering and frequency analysis.

Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: text (str): The text to analyze or process. max_keywords (int): The max keywords to analyze or process. min_word_length (int): The min word length to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYes
api_keyNo
max_keywordsNo
min_word_lengthNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.1/5.0
Behavior5/5

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

Despite no annotations, the description comprehensively details side effects (read-only, no side effects), authentication requirements, rate limits, error handling, idempotency, and data privacy. This fully informs the agent of behavioral traits.

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 well-structured with clear sections and front-loads the core purpose. However, it is somewhat verbose, especially the parameter descriptions that could be condensed. Overall, it organizes information effectively.

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 description covers behavioral aspects thoroughly but omits explanation of the output format, despite an output schema existing. It also lacks parameter-level constraints. Given the complexity and lack of annotations, it is nearly complete but missing output details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The 'Args' section simply repeats the parameter names with generic descriptions like 'The text to analyze or process.' for each, adding no meaningful constraints or context beyond the schema. With 0% schema coverage, the description fails to compensate, leaving parameters poorly documented.

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 extracts top keywords using TF-IDF, stop word filtering, and frequency analysis. It distinguishes itself from siblings like analyze_density and compare_keywords by focusing on extraction rather than comparison or density analysis.

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 includes explicit 'When to use' and 'When NOT to use' sections, providing guidance on appropriate contexts. However, it does not directly compare to sibling tools, and the 'When to use' text is somewhat generic, not specifically tied to keyword extraction.

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

suggest_tagsA

Suggest tags and categories for content based on keyword analysis and topic matching.

Behavior: This tool is read-only and stateless — it produces analysis output without modifying any external systems, databases, or files. Safe to call repeatedly with identical inputs (idempotent). Free tier: 10/day rate limit. Pro tier: unlimited. No authentication required for basic usage.

When to use: Use this tool when you need structured analysis or classification of inputs against established frameworks or standards.

When NOT to use: Not suitable for real-time production decision-making without human review of results.

Args: text (str): The text to analyze or process. max_tags (int): The max tags to analyze or process. api_key (str): The api key to analyze or process.

Behavioral Transparency: - Side Effects: This tool is read-only and produces no side effects. It does not modify any external state, databases, or files. All output is computed in-memory and returned directly to the caller. - Authentication: No authentication required for basic usage. Pro/Enterprise tiers require a valid MEOK API key passed via the MEOK_API_KEY environment variable. - Rate Limits: Free tier: 10 calls/day. Pro tier: unlimited. Rate limit headers are included in responses (X-RateLimit-Remaining, X-RateLimit-Reset). - Error Handling: Returns structured error objects with 'error' key on failure. Never raises unhandled exceptions. Invalid inputs return descriptive validation errors. - Idempotency: Fully idempotent — calling with the same inputs always produces the same output. Safe to retry on timeout or transient failure. - Data Privacy: No input data is stored, logged, or transmitted to external services. All processing happens locally within the MCP server process.

ParametersJSON Schema
NameRequiredDescriptionDefault
textYes
api_keyNo
max_tagsNo

Output Schema

ParametersJSON Schema
NameRequiredDescription
resultYes

TDQS

A4.1/5.0
Behavior5/5

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

The description thoroughly discloses behavioral traits: read-only, stateless, idempotent, authentication requirements, rate limits, error handling, and data privacy. Since no annotations are provided, the description fully carries the burden and does so exceptionally.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is well-structured with clear sections but contains redundancy (behavior details repeated in both the 'Behavior' paragraph and the 'Behavioral Transparency' section). It could be more concise.

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 output schema exists, the description covers behavior, usage, and error handling comprehensively. The weak parameter descriptions are a minor gap, but overall completeness is strong.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The Args section repeats parameter names with trivial descriptions (e.g., 'text (str): The text to analyze or process.'), adding no meaningful insight beyond the schema titles. With 0% schema description coverage, the description fails to compensate adequately.

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: 'Suggest tags and categories for content based on keyword analysis and topic matching.' This provides a specific verb and resource, and distinguishes it from sibling tools like analyze_density or extract_keywords.

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 includes explicit 'When to use' and 'When NOT to use' sections, giving clear context and exclusion criteria (not suitable for real-time production without human review). However, it does not mention alternatives or sibling tools.

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

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 4 tool updatesv1.0.0
    • First observedanalyze_density
    • First observedcompare_keywords
    • First observedextract_keywords
    • First observedsuggest_tags
Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.3/5.0

Scored across 4 tools

Disambiguation5/5

Each tool targets a distinct aspect of keyword analysis: density, comparison, extraction, and tagging. No two tools have overlapping purposes, making it easy for an agent to select the correct one.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern using snake_case (analyze_density, compare_keywords, extract_keywords, suggest_tags). No mixing of conventions.

Tool Count5/5

With 4 tools, the server is tightly scoped to keyword extraction and analysis. Each tool serves a clear need without bloat or deficiency.

Completeness4/5

The toolset covers the main keyword workflows: extraction, density, comparison, and tagging. A minor gap is the lack of a tool for keyphrase extraction or batch processing, but it's adequate for its purpose.

Maintenance

ActivityMaintained
ResponsivenessNo issues

Resources

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