Icypeas MCP Server
Provides containerization support for easier deployment and isolated execution of the MCP server
Used for managing environment variables, particularly the Icypeas API key needed for authentication
Used for package management and running build/start commands for the MCP server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@Icypeas MCP Serverfind John Doe's work email at Acme Corporation"
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.
Icypeas MCP Server
This is a Model Context Protocol (MCP) server that integrates with the Icypeas API to provide work email finding capabilities.
Features
Find work emails using name and company information
Related MCP server: Hatch MCP Server
Setup
Local Setup
Clone this repository
Install dependencies:
npm installCreate a
.envfile based on.env.exampleand add your Icypeas API key:ICYPEAS_API_KEY=your_api_key_hereBuild the server:
npm run buildStart the server:
npm start
Docker Setup
Clone this repository
Create a
.envfile with your Icypeas API keyBuild and run using Docker Compose:
docker-compose up -d
MCP Configuration
To use this server with an MCP client, add the following configuration to your MCP settings file:
{
"mcpServers": {
"icypeas": {
"command": "node",
"args": ["path/to/icypeas/dist/index.js"],
"env": {
"ICYPEAS_API_KEY": "your_api_key_here"
},
"disabled": false,
"autoApprove": []
}
}
}Available Tools
icypeas_find_work_email: Find a work email using name and company information
License
ISC
Available Tools
1 toolicypeas_find_work_emailC
Find a work email using name and company information.
| Name | Required | Description | Default |
|---|---|---|---|
| domainOrCompany | Yes | The domain or company name | |
| firstname | Yes | The first name of the person | |
| lastname | Yes | The last name of the person |
TDQS
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 mentions 'Find a work email' but doesn't explain how it works (e.g., search method, data sources), success rates, error handling, or privacy considerations. This leaves significant gaps in understanding the tool's behavior and reliability.
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 a single, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and easy to parse, making it highly concise and well-structured for quick understanding.
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 lack of annotations and output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., email format, confidence scores) or behavioral aspects like rate limits or data sources. For a tool that likely involves external data lookups, more context is needed to use it effectively.
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 input schema has 100% description coverage, clearly documenting all three required parameters. The description adds minimal value beyond the schema by implying the parameters are used together to find an email, but it doesn't provide additional context like format examples or usage tips. This meets the baseline for high schema coverage.
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's purpose: 'Find a work email using name and company information.' It specifies the verb ('Find'), resource ('work email'), and required inputs, making it easy to understand what the tool does. However, since there are no sibling tools, it cannot distinguish from alternatives, 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.
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, prerequisites, or limitations. It simply states what the tool does without context about its applicability, such as when it's most effective or any constraints on the data it can handle.
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. Dates show when Glama detected each change.
1 tool update
v1.0.0- First observed
icypeas_find_work_email
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly distinct as it is the only one available.
The single tool name follows a consistent snake_case pattern with a clear verb_noun structure (find_work_email). Since there is only one tool, naming consistency is inherently perfect.
One tool is too few for a server's apparent scope, as it suggests a very limited functionality that may not support typical agent workflows. This feels thin and incomplete for a general-purpose server.
The server's domain appears to be email or contact lookup, but with only one tool, there are significant gaps. For example, there are no tools for verifying emails, updating contact information, or handling other related operations, which will likely cause agent failures in broader tasks.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Related MCP Connectors
Model Context Protocol server for Studex tools, notifications, and profile integrations
Model Context Protocol server for todo.vu task management and time tracking.
A Model Context Protocol server for Wix AI tools
MCP server for Tomba email finder, verification, and contact enrichment API
Related MCP Servers
- AlicenseAqualityDmaintenanceA Model Context Protocol server that provides a seamless email management interface through Claude, allowing users to search, read, and send emails directly through natural language conversations.4114MIT
- FlicenseAqualityDmaintenanceA Model Context Protocol server for Hatch API integration that provides tools for finding and verifying contact information including emails, phone numbers, LinkedIn profiles, and company data.51-
- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol server that integrates with Prospeo API to find work emails and enrich LinkedIn profiles.1-
- FlicenseNot gradedqualityDmaintenanceA Model Context Protocol server that connects to RocketReach API, enabling AI assistants to find professional/personal emails, phone numbers, and enrich company data.1-
Appeared in Searches
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/Meerkats-Ai/icypeas-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server