Skip to main content
Glama
OnStartups

Agent.ai MCP Server

by OnStartups

comprehensive_contact_intelligence

Analyze email exchanges to extract relationship health, risk, and opportunities. Enrich with LinkedIn profiles and company news for actionable meeting intelligence.

Instructions

Uncover relationship health, discover opportunities, fill information gaps, and receive synthesized, actionable intelligence for key meetings or deal prep.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_providerYesEmail service to use. Supports Gmail and Outlook Mail.gmail
email_listNoComma-separated email addresses (e.g., john@acme.com, jane@company.com)
name_company_listNoFormat: 'Name, Company; Name, Company' (e.g., John Smith, Acme Corp; Jane Doe, Company Inc)
analyze_relationshipsNoExtract and synthesize commitments, risk, sentiment, and opportunity signals from email exchanges.
enrich_linkedinNoAugment with summary, recent activity, and conversation hooks from LinkedIn if available.
enrich_companyNoBring in latest news, funding, and exec moves for associated companies with AI research.
output_variable_nameYesVariable name to store the fully synthesized contact/meeting intelligence report.final_attendee_analysis
Behavior2/5

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

No annotations provided, so description carries full burden. It uses marketing language ('uncover', 'discover', 'synthesized') without disclosing data sources, side effects, or limitations. Does not clarify what actions it performs (e.g., reads emails, scrapes LinkedIn).

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 a single sentence, which is concise but overly vague. It front-loads action verbs but lacks specific detail. Every word feels generic rather than earning its place.

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 (7 parameters, multiple boolean toggles, no output schema), the description is insufficient. It does not explain output format, interaction between flags, or prerequisites. The description is too incomplete for an agent to reliably use.

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 covers 100% of parameters with good descriptions, enums, and defaults. The tool description adds no additional meaning beyond the high-level purpose; it does not elaborate on how parameters relate or should be combined.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose3/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states it generates synthesized intelligence for meetings/deal prep, but it is vague and does not clearly differentiate from sibling tools like 'enrich_person', 'contact_research', or 'meeting_prep_*' tools. Lacks a specific verb-resource pair.

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?

No guidance on when to use this tool versus alternatives. No when-not-to-use or exclusions provided. Among many similar tools, this omission reduces clarity for selection.

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

Install Server

Other Tools

Latest Blog Posts

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/OnStartups/agentai-mcp-server'

If you have feedback or need assistance with the MCP directory API, please join our Discord server