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MisarReach MCP Server

search_leads

Start an AI lead-search job and return its jobId immediately.

This is ASYNCHRONOUS: results are not in the response. Poll get_search_job_status with the jobId until it reports completion, then read the leads with list_leads filtered by that job_id. Use it to find NEW leads; use list_leads for ones already saved.

CONSUMES SEARCH CREDITS on every call, and each call starts a separate job — do not retry it as a way to check progress. Requires an API key. Setting useAI additionally spends AI credits to enrich and score the results as they arrive.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch query describing the ideal lead (2-200 chars)
useAINoUse AI to enrich and score results (default false)
filtersNoOptional filters

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior5/5

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

Adds substantial behavior beyond the annotations (which only cover readOnly/idempotent/destructive/openWorld): credit consumption on every call, one job per call, API key requirement, and the extra AI-credit spend implied by useAI. This is exactly the cost/side-effect context an agent needs before calling a non-idempotent job starter.

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?

Front-loaded with the action and return value, then workflow, then usage routing, then cost caveats. Four dense sentences with no filler; the async warning is capitalized and unmissable.

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

Completeness5/5

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

For an asynchronous job-starter with no output schema, the description supplies the missing pieces: what comes back now (jobId), how to get results, and the credit/key prerequisites. Nothing needed to invoke or follow up correctly is absent.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3, but the description meaningfully upgrades useAI by disclosing that it spends AI credits to enrich and score results as they arrive — a cost implication the schema does not state. The nested filters object gets no added semantics, keeping this short of a 5.

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?

States a specific verb+resource ('Start an AI lead-search job') and the immediate return value ('jobId'), which is unusually precise. It differentiates itself from list_leads explicitly, but the sibling search_verified_leads (another lead-search entry point) is never mentioned, so partial sibling disambiguation.

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

Usage Guidelines5/5

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

Gives the full when/when-not picture: use this for NEW leads, use list_leads for saved ones, do not retry this call to check progress, and poll get_search_job_status then list_leads with the job_id. Alternatives and the reason to avoid retrying are stated explicitly.

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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