Clado MCP Server
# Clado MCP Server
This is an official Model Context Protocol (MCP) Server for Clado.
For detailed API documentation and usage examples, visit the [official Clado documentation](https://docs.clado.ai/).
More information about the Model Context Protocol can be found [here](https://modelcontextprotocol.io/introduction).
## Table of Contents
- [Installation](#installation)
- [Usage](#usage)
- [Tools](#tools)
- [Configuration](#configuration)
- [License](#license)
## Installation
### Manual Installation
To install the server, run:
```bash
npx @clado-ai/mcp <YOUR-CLADO-API-KEY>
```
## Running on Cursor
Add to `~/.cursor/mcp.json` like this:
```json
{
"mcpServers": {
"clado": {
"command": "npx",
"args": ["-y", "@clado-ai/mcp"],
"env": {
"CLADO_API_KEY": "YOUR-API-KEY"
}
}
}
}
```
## Running on Windsurf
Add to your `./codeium/windsurf/model_config.json` like this:
```json
{
"mcpServers": {
"clado": {
"command": "npx",
"args": ["-y", "@clado-ai/mcp"],
"env": {
"CLADO_API_KEY": "YOUR-API-KEY"
}
}
}
}
```
## Claude Desktop app
This is an example config for the Clado MCP server for the Claude Desktop client.
```json
{
"mcpServers": {
"clado": {
"command": "npx",
"args": ["--yes", "@clado-ai/mcp"],
"env": {
"CLADO_API_KEY": "your-api-key"
}
}
}
}
```
## Tools
* `search_for_users` - Search for LinkedIn users with filters like query, school, and match threshold
* `enrich_linkedin` - Retrieves detailed profile information for a specific LinkedIn URL (1 credit per lookup)
* `retrieve_contacts` - Retrieves email addresses and phone numbers for LinkedIn profiles, supports reverse lookup via email/phone (4 credits for email, 10 credits for phone if found)
* `scrape_linkedin` - Retrieves detailed profile data and posts with comments from a LinkedIn profile URL (2 credits per request)
* `linkedin_post_reactions` - Retrieves reactions and engagement data for a specific LinkedIn post URL
## License
This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
TDQS
Scored across 5 tools
The tools have some overlap in purpose, particularly between 'enrich_linkedin' and 'scrape_linkedin', which both retrieve LinkedIn profile data, though 'scrape_linkedin' includes posts and comments. 'retrieve_contacts' focuses on contact information, while 'linkedin_post_reactions' and 'search_for_users' are more distinct. Descriptions help differentiate them, but confusion could arise between the profile-focused tools.
Most tools follow a consistent verb_noun pattern (e.g., 'enrich_linkedin', 'scrape_linkedin', 'search_for_users'), which is clear and predictable. However, 'retrieve_contacts' uses 'retrieve' instead of a more aligned verb like 'get' or 'enrich', causing a minor deviation. Overall, the naming is mostly consistent and readable.
With 5 tools, the count is well-scoped for a LinkedIn-focused server, covering key operations like profile enrichment, contact retrieval, post analysis, and user search. Each tool appears to serve a distinct purpose, and the number is neither too sparse nor overwhelming for the domain.
The tool set covers core LinkedIn data retrieval functions, including profile enrichment, contact information, post engagement, and user search. Minor gaps exist, such as the lack of tools for updating or managing data (e.g., no 'create_contact' or 'delete_profile'), but agents can likely work around these for typical lookup and analysis tasks.