Skip to main content
Glama
OnStartups

Agent.ai MCP Server

by OnStartups

fetch_relevant_gmail_threads

Search a contact's email history to find relevant discussions, extract interaction patterns, and generate actionable insights for upcoming meetings.

Instructions

Search a contact's email history for relevant discussions, extract interaction patterns, timelines, and generate actionable insights based on contact and meeting details.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
email_providerYesEmail service to search. Supports Gmail and Outlook Mail.gmail
contact_emailNoThe email address to search for (e.g., john@example.com). Will search in from, to, and cc fields.
meeting_topicNoTopic or keywords to search for in emails (e.g., 'Q4 pricing proposal'). AI will extract relevant keywords.
date_range_daysYesHow far back to search for emails.90
max_resultsYesMaximum number of email threads to retrieve (e.g., 10, 50, 100).10
analysis_typeYesOptional AI analysis to run on the fetched emails.none
output_variable_nameYesProvide a variable name to store the Gmail threads, like 'topic_relevant_gmail_threads' or 'contact_emails'.topic_relevant_gmail_threads
Behavior3/5

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

With no annotations, the description carries full burden. It mentions 'search' and 'extract' but does not disclose authentication needs, rate limits, or that the tool may require Gmail/Outlook access. The AI analysis aspect is only partially covered.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is a single, concise sentence with no unnecessary words. It front-loads the main action.

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?

Despite having 7 parameters and no output schema, the description fails to mention that results are stored in a variable (via output_variable_name). It does not describe the output format or provide enough context for a complex tool.

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 baseline is 3. The main description adds no additional meaning beyond the schema; the parameter descriptions in the schema are already detailed.

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

Purpose5/5

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

The description clearly states the tool's action ('Search a contact's email history') and resource ('email history'), with additional objectives like extracting patterns and generating insights. It distinguishes itself from sibling tools, which are not email-specific.

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

Usage Guidelines3/5

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

The description implies usage for finding relevant emails from a contact based on meeting details, but lacks explicit guidance on when to use this over alternatives or when not to use it. No exclusions or prerequisites are mentioned.

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