MatchAwards MCP server

Official

by matchawards

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Python

Hybrid

Get opportunity details

get_opportunity

Read-onlyIdempotent

Retrieve full details for a specific search result by ID, including description, published contacts, and AI-generated notes to help identify contacts and evaluate opportunities.

Instructions

Use this when the user wants the details of one search result, or who to contact about it.

Pass the id from a search result. Returns the result's row plus its description (up to 2000 characters), published points of contact (name and title only) and, when MatchAwards has them, ai: AI-generated notes (subcontracting and large-prime angles) and a summary. AI text is AI-generated: label it as such whenever you quote it. Example: id="117402307943537453".

Print url, and sam_url for federal notices, as markdown links.

Do not use for searching (search_contracts, search_grants, search_jobs), for fit or bid/no-bid questions (assess_opportunity) or for contact details beyond the published names and titles.

Input Schema

Name	Required	Description	Default
`id`	Yes	The id field of a search result.

Output Schema

Name	Required	Description
`ai`	No	AI-generated notes on this opportunity, or null. Label them as AI-generated when you show or quote them.
`id`	Yes	Pass to get_opportunity for the description and contacts.
`url`	No	The posting on matchawards.com. Show it as a markdown link.
`city`	No
`note`	No
`type`	No	federal, state, grant or job.
`as_of`	No
`naics`	No	On state notices (type state) the naics code itself is AI-assigned.
`state`	No
`title`	No
`agency`	No
`office`	No
`sam_url`	No	The SAM.gov notice (federal only). Show it as a markdown link.
`contacts`	No	Published points of contact; [] if none.
`agency_id`	No	The agency's MatchAwards id.
`posted_at`	No	Date, YYYY-MM-DD.
`set_aside`	No
`description`	No	Up to 2000 characters.
`matched_naics`	No	Only when you filtered by naics: the requested codes this record carries: its own code (in naics) or, for a grant or job, another code of its program or occupation.
`ai_matched_naics`	No	Only when you filtered by naics: requested codes this contract notice matched only because MatchAwards' AI suggested them, not its own codes. Call such a match AI-suggested.
`no_fixed_deadline`	No	true: the deadline is a placeholder date.
`response_deadline`	No	Date, YYYY-MM-DD; null if none.
`solicitation_number`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Nov 7, 2026

TDQS

A4.8/5.0

Behavior5/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description adds substantially more: the 2000-character truncation of description, that AI notes are optional ('when MatchAwards has them'), and a required labeling caveat for AI-generated text. It also specifies output presentation duties (markdown links for url/sam_url), which annotations cannot convey.

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?

Front-loaded with the when-to-use sentence, followed by ordered operational notes (id provenance, return contents, AI labeling, link formatting, exclusions). Every sentence is actionable, though the formatting directive is a slight extension beyond core tool semantics.

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?

An output schema exists, yet the description still summarizes the payload and flags the AI-generated caveat, which is the one thing an agent could misuse. Combined with explicit routing to siblings, an agent has everything needed to call this correctly.

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% and the pattern is documented, so the description only needs to add value; it does by stating the id must come from a search result and giving a concrete example id. Marginal gain over the schema, so not a 5.

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?

States a specific verb and resource ('details of one search result') and explicitly scopes what is returned (row, description up to 2000 chars, contacts, optional AI notes). It is clearly distinguishable from search_* and assess_opportunity because it retrieves a single known id rather than searching or evaluating.

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 an explicit trigger ('when the user wants the details of one search result, or who to contact about it'), explicit anti-triggers (not for searching, not for fit/bid questions, not for deeper contact details), and names the alternatives to use instead (search_contracts, search_grants, search_jobs, assess_opportunity).

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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