What can you do with this server?

This MCP server enables natural language querying of Erick Wendel's contributions (talks, blog posts, and videos) through AI tools like Claude and Cursor. Core Tools: * get_talks: Filter by ID, title, language (Spanish/English/Portuguese), city, country, or year; supports pagination, count-only mode, and aggregated grouping by language/country/city * get_posts: Filter by ID, title, language, or portal with pagination support * get_videos: Filter by ID, title, or language with pagination * check_status: Verify API health and availability Prompts: * find-content: Generate queries to locate specific content by type, topic, and language * summarize-activity: Create content activity summaries by year Resources: * erickwendel://about: Server information and capabilities metadata * erickwendel://statistics: Content statistics and available queries Integration & Development: * Compatible with Claude Desktop, Cursor IDE, and MCPHost (with Ollama) * Easy setup via npx without installation * Type-safe TypeScript with Zod validation, modular architecture, and structured error handling

Which integrations are available for this server?

Integrates with a GraphQL API at tml-api.herokuapp.com to fetch data about Erick Wendel's talks, posts, and videos with filtering capabilities Connects to a GraphQL API hosted on Heroku to fetch and filter Erick Wendel's contributions data Runs natively in Node.js environment without transpilation, providing tools for querying Erick Wendel's content Supports integration with Ollama through MCPHost as a free alternative to Claude, enabling LLMs to interact with the MCP server Built with TypeScript for type safety, with native support in Node.js without requiring transpilation Uses Zod schema validation to ensure type safety and proper data validation for API requests and responses

How do I use Erick Wendel Contributions MCP?

1. Click on "Install Server". 2. Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state. 3. In the chat, type @ followed by the MCP server name and your instructions, e.g., "@Erick Wendel Contributions MCP show me talks about Node.js in Portuguese" That's it! The server will respond to your query, and you can continue using it as needed. Here is a step-by-step guide with screenshots.

en es ja ko zh

Erick Wendel Contributions MCP

by ErickWendel

Overview Schema Related Servers Score Discussions

TypeScript

Hybrid

erickwendel-contributions-mcp

CI Status npm version npm downloads

A Model Context Protocol (MCP) server that provides tools to query Erick Wendel's contributions across different platforms. Query talks, blog posts, and videos using natural language through Claude, Cursor or similars. This project was built using Cursor IDE with the default agent (trial version).

Quick Start

Use this MCP server directly with Claude Desktop or Cursor without installation:

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "npx",
      "args": ["-y", "@erickwendel/contributions-mcp"]
    }
  }
}

Add this configuration to:

Claude Desktop: ~/Library/Application Support/Claude/claude_desktop_config.json (macOS)
Cursor: ~/.cursor/mcp.json

Related MCP server: MCP TabNews Integration

Available Tools

This MCP server provides the following capabilities:

Tools

get-talks: Retrieves a paginated list of talks with optional filtering
- Supports filtering by ID, title, language, city, country, and year
- Can return counts grouped by language, country, or city
get-posts: Fetches posts with optional filtering and pagination
- Supports filtering by ID, title, language, and portal
get-videos: Retrieves videos with optional filtering and pagination
- Supports filtering by ID, title, and language
check-status: Verifies if the API is alive and responding

Prompts

find-content: Generate queries to find specific content by type, topic, and language
summarize-activity: Create summaries of content activity by year

Resources

erickwendel://about: Server information and capabilities metadata
erickwendel://statistics: Content statistics and available queries

Integration with AI Tools

Inspect MCP Server Capabilities

You can inspect this MCP server's capabilities using the MCP Inspector:

npm run inspect

This will show you all available tools, their parameters, and how to use them.

Setup

Make sure you're using Node.js v20+

node -v
# v20.x.x or higher

Clone this repository:

git clone https://github.com/erickwendel/erickwendel-contributions-mcp.git
cd erickwendel-contributions-mcp

Install dependencies:

npm ci

Run the server:

npm start

Integration with AI Tools

Cursor Setup

Add the following configuration to ~/.cursor/mcp.json:

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "npx",
      "args": ["-y", "@erickwendel/contributions-mcp"]
    }
  }
}

Make sure Cursor chat is in Agent mode by selecting "Agent" in the lower left side dropdown, then ask "how many videos were published about JavaScript in 2024":

Local Development

For local development, use the absolute path to the project:

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "node",
      "args": ["--experimental-strip-types", "ABSOLUTE_PATH_TO_PROJECT/src/index.ts"]
    }
  }
}

Claude Desktop Setup

Go to Claude settings
Click in the Developer tab
Click in edit config
Open the config in a code editor
Add the following configuration to ~/Library/Application Support/Claude/claude_desktop_config.json (macOS):

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "npx",
      "args": ["-y", "@erickwendel/contributions-mcp"]
    }
  }
}

Local Development

For local development, use the absolute path to the project:

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "node",
      "args": ["--experimental-strip-types", "ABSOLUTE_PATH_TO_PROJECT/src/index.ts"]
    }
  }
}

MCPHost with Ollama (Free Alternative)

If you don't have access to Claude Desktop or Cursor, you can use MCPHost with Ollama as a free alternative.

Install MCPHost:

go install github.com/mark3labs/mcphost@latest

Create a config file (e.g. ./mcp.jsonc):

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "npx",
      "args": ["-y", "@erickwendel/contributions-mcp"]
    }
  }
}

Run with Ollama:

ollama pull MODEL_NAME
mcphost --config ./mcp.jsonc -m ollama:MODEL_NAME

Local Development

For local development, update the config:

{
  "mcpServers": {
    "erickwendel-contributions": {
      "command": "node",
      "args": ["--experimental-strip-types", "ABSOLUTE_PATH_TO_PROJECT/src/index.ts"]
    }
  }
}

Example Queries

Here are some examples of queries you can ask Claude, Cursor or any MCP Client:

"How many talks were given in 2023?"

"Show me talks in Spanish"

"Find posts about WebXR"

Development

Features

Built with Model Context Protocol (MCP)
Full MCP Capabilities: Tools, Prompts, and Resources
Type-safe with TypeScript and Zod schema validation
Native TypeScript support in Node.js without transpilation
Generated SDK using GenQL
Modular architecture with separation of concerns
Standard I/O transport for easy integration
Structured error handling
Compatible with Claude Desktop, Cursor, and MCPHost (free alternative)

Note: This project requires Node.js v23+ as it uses the native TypeScript support added in the last year.

Architecture

The codebase follows a modular structure:

src/
  ├── config/      # Configuration settings
  ├── types/       # TypeScript interfaces and types
  ├── tools/       # MCP tool implementations
  ├── utils/       # Utility functions
  ├── services/    # API service layer
  └── index.ts     # Main entry point

Testing

To run the test suite:

npm test

For development mode with watch:

npm run test:dev

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Author

Erick Wendel

License

This project is licensed under the MIT License - see the LICENSE file for details.

Available Tools

4 tools

check_statusB

Check if the API is alive and responding.

ParametersJSON Schema

Name	Required	Description	Default
No parameters

TDQS

B3.2/5.0

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool checks API status but doesn't add context such as what 'alive and responding' entails (e.g., response time, error handling), rate limits, or authentication needs. This leaves significant gaps for a tool with no structured safety hints.

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, efficient sentence that directly states the tool's purpose without any waste. It's front-loaded and appropriately sized for a simple tool, making it easy for an agent to parse quickly.

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 the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate. It covers the basic purpose but lacks details on behavior, usage context, or output expectations, which could be helpful for an agent to understand the full scope of this health check tool.

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 has 0 parameters with 100% coverage, so no parameter documentation is needed. The description appropriately doesn't discuss parameters, earning a baseline score of 4 for not adding unnecessary information beyond the schema.

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's purpose with a specific verb ('check') and resource ('API'), explaining it verifies if the API is alive and responding. However, it doesn't distinguish this from its siblings (get_posts, get_talks, get_videos), which appear to be data retrieval tools, so it misses explicit differentiation.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for health checks but provides no explicit guidance on when to use this tool versus alternatives. There's no mention of prerequisites, timing, or comparison to sibling tools, leaving the agent to infer context without clear direction.

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

get_postsB

Get a list of posts with optional filtering and pagination.

ParametersJSON Schema

Name	Required	Description
`id`	No	Filter posts by ID
`title`	No	Filter posts by title
`language`	No	Filter posts by language
`portal`	No	Filter posts by portal
`skip`	No	Number of posts to skip
`limit`	No	Maximum number of posts to return

TDQS

B3.1/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It states the tool retrieves a list with filtering and pagination but doesn't cover critical aspects like whether it's read-only, rate limits, authentication needs, error handling, or what the return format looks like (e.g., JSON structure). This leaves significant gaps for an agent to understand the tool's behavior.

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, efficient sentence that front-loads the core purpose ('Get a list of posts') and adds essential qualifiers ('with optional filtering and pagination') without any wasted words. It's appropriately sized for the tool's complexity.

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 the tool's moderate complexity (6 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers the basic purpose and hints at parameter usage but lacks details on behavioral traits, return values, and sibling differentiation, making it minimally viable but with clear gaps.

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?

The description mentions 'optional filtering and pagination,' which aligns with parameters like 'id', 'title', 'skip', and 'limit' in the schema. However, with 100% schema description coverage, the schema already fully documents all 6 parameters, so the description adds minimal value beyond reinforcing the general purpose of filtering and pagination.

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 verb ('Get') and resource ('list of posts'), making the purpose unambiguous. However, it doesn't differentiate from sibling tools like 'get_talks' or 'get_videos' beyond mentioning posts specifically, so it lacks explicit sibling distinction.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'optional filtering and pagination' but provides no guidance on when to use this tool versus alternatives like 'get_talks' or 'get_videos', nor does it specify any prerequisites or exclusions for usage.

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

get_talksC

Get a list of talks with optional filtering and pagination.

ParametersJSON Schema

Name	Required	Description
`id`	No	Filter talks by ID
`title`	No	Filter talks by title
`language`	No	Filter talks by language (e.g., 'spanish', 'english', 'portuguese' or direct codes like 'es', 'en', 'pt-br')
`city`	No	Filter talks by city
`country`	No	Filter talks by country
`year`	No	Filter talks by year
`skip`	No	Number of talks to skip
`limit`	No	Maximum number of talks to return
`count_only`	No	If true, returns only the count without talk details
`group_by`	No	Group counts by a specific field (language, country, city)

TDQS

C2.9/5.0

Behavior2/5

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 mentions 'optional filtering and pagination' but lacks critical behavioral details: what the return format looks like (e.g., list structure, fields included), whether it's a safe read operation (implied by 'Get' but not explicit), error handling, rate limits, or authentication requirements. For a tool with 10 parameters and no annotation coverage, this is insufficient.

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, efficient sentence: 'Get a list of talks with optional filtering and pagination.' It's front-loaded with the core purpose and wastes no words. Every part of the sentence earns its place by highlighting key features.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (10 parameters, no annotations, no output schema), the description is incomplete. It lacks details on return values, error conditions, behavioral traits (e.g., whether it's idempotent or safe), and usage context relative to siblings. For a list-retrieval tool with rich filtering options, more guidance is needed to help an agent use it effectively.

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 the schema fully documents all 10 parameters. The description adds minimal value beyond the schema—it mentions 'optional filtering and pagination,' which aligns with parameters like 'skip,' 'limit,' and filtering fields, but doesn't provide additional syntax, format details, or usage examples. Baseline 3 is appropriate when the schema does the heavy lifting.

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's purpose: 'Get a list of talks with optional filtering and pagination.' It specifies the verb ('Get') and resource ('talks'), and mentions key capabilities (filtering, pagination). However, it doesn't explicitly differentiate from sibling tools like 'get_posts' or 'get_videos' beyond the resource type.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. It mentions 'optional filtering and pagination' but doesn't specify scenarios, prerequisites, or exclusions. With sibling tools like 'get_posts' and 'get_videos' available, there's no indication of when to choose talks over posts or videos.

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

get_videosC

Get a list of videos with optional filtering and pagination.

ParametersJSON Schema

Name	Required	Description
`id`	No	Filter videos by ID
`title`	No	Filter videos by title
`language`	No	Filter videos by language
`skip`	No	Number of videos to skip
`limit`	No	Maximum number of videos to return

TDQS

C2.9/5.0

Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions filtering and pagination but fails to describe critical behaviors like whether this is a read-only operation, what permissions are needed, rate limits, error handling, or the format of returned data. For a tool with 5 parameters and no annotations, this is inadequate.

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, efficient sentence that front-loads the core purpose ('Get a list of videos') and adds key features ('with optional filtering and pagination') without any wasted words. It's appropriately sized for the tool's complexity.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's moderate complexity (5 parameters, no annotations, no output schema), the description is insufficient. It lacks details on behavioral traits, output format, error conditions, and differentiation from siblings. While the schema covers parameters well, the description doesn't compensate for missing annotations and output schema, leaving the agent with incomplete context.

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?

The description adds minimal value beyond the input schema, which has 100% coverage with clear parameter descriptions. It mentions 'optional filtering and pagination' which aligns with parameters like 'id', 'title', 'language', 'skip', and 'limit', but doesn't provide additional semantic context or usage examples. Baseline 3 is appropriate given the schema's thoroughness.

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 action ('Get a list of videos') and resource ('videos'), making the purpose understandable. However, it doesn't distinguish this tool from potential siblings like 'get_posts' or 'get_talks' beyond the resource type, which prevents a perfect score.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description mentions 'optional filtering and pagination' which implies some usage context, but provides no explicit guidance on when to use this tool versus alternatives like 'get_posts' or 'get_talks', nor any prerequisites or exclusions. This leaves significant gaps in usage direction.

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

Install Server

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TDQS

B3.4/5.0

Disambiguation5/5

Each tool has a clearly distinct purpose targeting different resource types: API status, posts, talks, and videos. There is no overlap in functionality, making it easy for an agent to select the correct tool without confusion.

Naming Consistency5/5

All tool names follow a consistent verb_noun pattern (check_status, get_posts, get_talks, get_videos), using snake_case throughout. This predictability enhances readability and usability for agents.

Tool Count4/5

With 4 tools, the count is reasonable for a contributions-focused server, covering status and three content types. It feels slightly thin but well-scoped, as each tool serves a distinct purpose without unnecessary bloat.

Completeness3/5

The toolset provides read-only access to posts, talks, and videos with filtering and pagination, which is adequate for retrieval. However, there are notable gaps: no create, update, or delete operations, limiting full lifecycle management of contributions in the domain.

Maintenance

ActivityInactive

ResponsivenessSyncing

Resources

Need Help?

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Quick Start

Available Tools

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Integration with AI Tools

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