Remote MCP server to enrich company profiles with structured B2B data and confidence scores.
Glama MCP Gateway
Connect through Glama MCP Gateway for full control over tool access and complete visibility into every call.
Full call logging
Every tool call is logged with complete inputs and outputs, so you can debug issues and audit what your agents are doing.
Tool access control
Enable or disable individual tools per connector, so you decide what your agents can and cannot do.
Managed credentials
Glama handles OAuth flows, token storage, and automatic rotation, so credentials never expire on your clients.
Usage analytics
See which tools your agents call, how often, and when, so you can understand usage patterns and catch anomalies.
Average 4.2/5 across 1 of 1 tools scored.
Only one tool exists, so there is no ambiguity—agents have no risk of selecting the wrong tool.
With a single tool, naming consistency is trivial; the tool name 'enrich_lead' is clear and follows a verb_noun pattern.
One tool for a 'B2B Lead Enrichment' server is borderline - it can work if the tool encapsulates all enrichment needs, but typically such servers benefit from multiple specialized tools (e.g., batch enrichment, search, status).
The tool covers multiple enrichment dimensions (firmographic, technographic, intent, contact), but lacks batch operations, updates, or status tracking, leaving significant gaps for common workflows.
enrich_leadAEnrich a B2B company profile with structured firmographic, technographic, intent, and contact data. This tool should be called when an AI agent needs to gather detailed information about a company before crafting a personalized outreach, generating a lead score, or making a sales recommendation.
| Name | Required | Description | Default |
|---|---|---|---|
| domain | Yes | The company domain to enrich (e.g., "stripe.com"). | |
| attributes | No | Which data attributes to include. Allowed values: firmographic, technographic, intent, contacts. | |
| requiredFields | No | Specific fields that must be present in the response. |
| Name | Required | Description |
|---|---|---|
| revenue | Yes | Estimated annual revenue range (e.g., "$1B+"). |
| contacts | No | Key contacts identified at the company. |
| industry | Yes | Primary industry classification. |
| insights | Yes | Actionable semantic insights derived from the data. |
| enrichedAt | Yes | ISO 8601 timestamp when this enrichment was performed. |
| companyName | Yes | Official legal name of the enriched company. |
| technologies | Yes | Technology stack associated with the company. |
| employeeCount | Yes | Estimated employee count range (e.g., "5000+"). |
| intentSignals | Yes | Signals showing buying intent or strategic initiatives. |
| confidenceScore | Yes | Confidence score from 0 to 1. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true. The description adds detail about the types of data collected (firmographic, technographic, intent, contacts). Although it doesn't mention error handling or auth, the read-only nature is clear.
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?
Two sentences that are front-loaded with purpose. No redundant information; every sentence is essential.
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 presence of an output schema (not shown) and full parameter descriptions, the tool definition is fairly complete. Missing are potential error conditions or rate limits, but overall it provides enough context for usage.
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?
Schema coverage is 100%, so baseline is 3. The description does not add significant semantic value beyond the schema; the parameter descriptions are self-contained. It hints at attribute categories but doesn't detail them.
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 verb 'Enrich' and resource 'B2B company profile' with specific data types (firmographic, technographic, etc.). It distinguishes the tool's purpose well, and with no sibling tools, it's unambiguous.
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 explicitly states when to use the tool: before personalized outreach, lead scoring, or sales recommendations. While it provides good context, it lacks when-not-to-use guidance or alternatives, but siblings are absent.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Claim this connector by publishing a /.well-known/glama.json file on your server's domain with the following structure:
{
"$schema": "https://glama.ai/mcp/schemas/connector.json",
"maintainers": [{ "email": "your-email@example.com" }]
}The email address must match the email associated with your Glama account. Once published, Glama will automatically detect and verify the file within a few minutes.
Control your server's listing on Glama, including description and metadata
Access analytics and receive server usage reports
Get monitoring and health status updates for your server
Feature your server to boost visibility and reach more users
For users:
Full audit trail – every tool call is logged with inputs and outputs for compliance and debugging
Granular tool control – enable or disable individual tools per connector to limit what your AI agents can do
Centralized credential management – store and rotate API keys and OAuth tokens in one place
Change alerts – get notified when a connector changes its schema, adds or removes tools, or updates tool definitions, so nothing breaks silently
For server owners:
Proven adoption – public usage metrics on your listing show real-world traction and build trust with prospective users
Tool-level analytics – see which tools are being used most, helping you prioritize development and documentation
Direct user feedback – users can report issues and suggest improvements through the listing, giving you a channel you would not have otherwise
The connector status is unhealthy when Glama is unable to successfully connect to the server. This can happen for several reasons:
The server is experiencing an outage
The URL of the server is wrong
Credentials required to access the server are missing or invalid
If you are the owner of this MCP connector and would like to make modifications to the listing, including providing test credentials for accessing the server, please contact support@glama.ai.
No comments yet. Be the first to start the discussion!
Sign in to create a connector for this server.
