Skip to main content
Glama
Program-Integrity-Alliance

PIA MCP Server

Official

pia_oversight_recommendations

Search open oversight recommendations from GAO and Oversight.gov with faceted filters by status, priority, agency, and theme. Get total counts, sample results, and a link to the full set.

Instructions

Search oversight recommendations (Open Recommendations dataset) with facets enabled by default. Today's date is 2026-06-25. This dataset contains recommendations from GAO and Oversight.gov only — SourceDocumentDataSource filters for any other source will be ignored. Do NOT filter by SourceDocumentDataSet — this tool already targets the 'Open Recommendations' dataset automatically. IMPORTANT: When a text query is provided, do NOT add a referenced_agencies filter — the query handles relevance matching. Only use referenced_agencies when the query is empty (pure filter/facet lookups). total_count is the number of OPEN recommendations matching the query and all applied filters — report it as that count. The results are a representative sample to summarize, and facets break the set down by status, priority, agency, and theme. Counts from free-text queries are approximate (semantic matching); pure filter or agency lookups are exact. Recommendations have no per-document citations, so it is very important to always include the govquery_url for the full set in Rec Spotlight rather than citing individual rows.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number (default: 1)
limitNoMaximum results limit
queryYesSearch query text
filterNoOptional OData filter expression supporting complex boolean logic. AVAILABLE FIELDS: • SourceDocumentDataSource: Data source/agency that published the document. Major sources (>1k documents): 'Department of Justice', 'Congress.gov', 'Oversight.gov', 'CRS', 'GAO', 'Federal Register' • SourceDocumentDataSet: Dataset or collection the document belongs to. Values include: 'reports', 'federal-reports', 'press-releases', 'executive orders', 'Open Recommendations'. Note: the value is 'Open Recommendations' (not 'recommendations'). Values: 'press-releases', 'bills-and-laws', 'reports', 'federal-reports', 'executive orders', 'state-and-local-reports', 'annual-financial-reports', 'congressional-justification-reports', 'performance-and-accountability-reports' • SourceDocumentTitle: Document title - use contains, eq for text matching • SourceDocumentPublishDate: Publication date - ISO 8601 format YYYY-MM-DD (e.g., '2023-01-01'). Use ge/le for ranges • RecStatus: Recommendation status • RecPriorityFlag: Priority flag for recommendations • SourceDocumentIsRecDoc: Whether the document contains recommendations. Values: 'No', 'Yes' • RecFraudRiskManagementThemePIA: Fraud risk management theme classification • RecMatterForCongressPIA: Whether the matter is for Congressional attention • RecRecommendation: Recommendation text - use contains, eq for text matching • RecAgencyComments: Agency comments on recommendations - use contains, eq for text matching • referenced_agencies: Agencies referenced by documents (collection field). IMPORTANT: Only use this filter when the query is empty (pure filter/facet lookups). Do NOT combine with a text query — the query already handles relevance matching. Example: (referenced_agencies/any(a: a eq 'Department of Defense (DOD)') or referenced_agencies/any(a: a eq 'Department of Justice (DOJ)')) - for single agency omit outer parentheses and 'or'. Get all values via pia_search with facets_only=true. OPERATORS: • Text: contains, eq, ne, startswith, endswith • Exact: eq (equals), ne (not equals), in (in list) • Date: ge (greater/equal), le (less/equal), eq (equals) • Logic: and, or, not, parentheses for grouping EXAMPLES: • "SourceDocumentDataSource eq 'GAO'" • "SourceDocumentDataSource eq 'GAO' and RecStatus ne 'Closed'" • "(SourceDocumentDataSource eq 'GAO' or SourceDocumentDataSource eq 'OIG') and RecStatus eq 'Open'" • "SourceDocumentPublishDate ge '2020-01-01' and SourceDocumentPublishDate le '2024-12-31'" TIP: Use pia_search with facets_only=true to get the most current available values. COMMON AGENCY NAMES (use EXACT spelling for referenced_agencies): Department of Defense (DOD), Department of Health and Human Services (HHS), Department of Homeland Security (DHS), Department of Justice (DOJ), Department of Education (ED), Department of Veterans Affairs (VA), Department of the Treasury, Department of Agriculture (USDA), Department of the Interior (DOI), Department of Transportation (DOT), Department of Energy (DOE), Department of State, Department of Labor (DOL), Department of Commerce (DOC), Department of Housing and Urban Development (HUD), Environmental Protection Agency (EPA), National Aeronautics and Space Administration (NASA), Social Security Administration (SSA), Small Business Administration (SBA), Office of Personnel Management (OPM), General Services Administration (GSA)
page_sizeNoResults per page (default: 100)
facets_onlyNoReturn ONLY the facet breakdown + total_count + Rec Spotlight govquery_url, omitting the individual recommendation rows — to see the open-rec population broken down by status/priority/agency/theme without pulling rows.
search_modeNoSearch mode (default: content)content
include_facetsNoInclude facets in results (default: true)

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
outputYes
Behavior5/5

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

With no annotations provided, the description carries the full burden and delivers richly: it discloses that SourceDocumentDataSource filters for non-GAO/Oversight.gov sources are ignored, that free-text counts are approximate while pure filter/agency lookups are exact, and that results are a representative sample with no per-document citations, requiring the govquery_url for the full set.

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 fairly long (~400 words) but front-loaded with the core purpose as the first clause. Most sentences earn their place given the tool's complexity, though the referenced_agencies warning in the description partially duplicates what the filter parameter schema already states.

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 a complex tool with 8 parameters, an output schema, and tricky usage rules, the description is remarkably complete: it defines total_count semantics, explains results/facets behavior, caveats approximate versus exact counts, and mandates the govquery_url citation rule. No significant gaps remain.

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?

All 8 parameters already have schema descriptions (100% coverage), so the baseline is 3. The description adds some value by explaining the GAO/Oversight.gov source restriction and reinforcing the query-versus-referenced_agencies interaction, but most parameter semantics are already covered in the schema.

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 opens with 'Search oversight recommendations (Open Recommendations dataset)' — a specific verb+resource with clearly defined scope. It distinguishes this tool from the general sibling pia_search by noting it automatically targets the Open Recommendations dataset and that SourceDocumentDataSet filtering is unnecessary.

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

Usage Guidelines4/5

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

The description provides explicit do/don't guidance: 'Do NOT filter by SourceDocumentDataSet', 'When a text query is provided, do NOT add a referenced_agencies filter', and 'Only use referenced_agencies when the query is empty'. However, it never names the sibling pia_search as an alternative for other use cases, so the when-to-use-vs-alternatives message is incomplete.

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/Program-Integrity-Alliance/pia-mcp-local'

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