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AvolveAi

Prosp MCP Server

by AvolveAi

Send LinkedIn Message

send_message

Send a LinkedIn message to any profile by providing the profile URL and message text. Optionally include a campaign ID to track outreach in Prosp.

Instructions

Send a LinkedIn message to a profile.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
paramsYesInput for sending a LinkedIn message.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv0.2.0

TDQS

B3.1/5.0
Behavior2/5

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

Annotations only provide destructiveHint=false, which is minimal. The description does not disclose that sending a message is a non-reversible side effect, that it may create a conversation, or any rate-limit or authentication expectations. No contradiction with annotations exists.

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

Conciseness5/5

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

The description is a single efficient sentence with no filler. It front-loads the action and resource clearly, and every word earns its place.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With an output schema present and full parameter coverage, the description is minimally viable. However, it lacks guidance on choosing between text and voice messaging, potential side effects, and any campaign context, making it incomplete for richer decision-making.

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 coverage is 100%, so the schema already documents linkedin_url, message, and campaign_id. The description adds no additional meaning about parameter semantics beyond what the schema provides, so the baseline 3 applies.

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

Purpose4/5

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

The description states a specific verb and resource: 'Send a LinkedIn message to a profile.' This is clear and actionable, and the input schema confirms it is a text message. It does not explicitly differentiate from the sibling send_voice_message, so it misses the top score.

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?

The description provides no guidance on when to use this tool versus alternatives like send_voice_message or when not to use it. It does not mention prerequisites, such as the lead being reachable or needing a valid LinkedIn URL.

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

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