Skip to main content
Glama
lzinga

US Government Open Data MCP

nih_projects_by_agency

Read-only

Retrieve project counts by NIH institute for a fiscal year to analyze funding distribution across disease areas.

Instructions

Get project counts by NIH institute/center for a fiscal year. Shows which institutes fund the most research: NCI (cancer), NIAID (infectious diseases), etc. Useful for understanding NIH budget allocation across disease areas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
fiscal_yearYesFiscal year: 2024
agenciesNoSpecific agency codes to check (default: top 25)
Behavior3/5

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

Annotations provide readOnlyHint, and the description adds context that this is a read operation showing counts, but does not disclose additional behavioral traits like pagination or rate limits.

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?

Two concise sentences that front-load the core purpose and provide an example, with no wasted words.

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

Completeness4/5

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

For a simple tool with two parameters and no output schema, the description adequately explains the output (project counts by institute) and use case, though it could explicitly describe the return format.

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% with clear descriptions and enums for agencies; the description adds minimal extra context (e.g., example agencies) but does not explain formatting or interpretation beyond 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 clearly states the tool gets project counts by NIH institute/center for a fiscal year, and distinguishes from siblings like nih_search_projects by focusing on aggregated counts rather than individual project details.

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 the tool is for high-level budget allocation analysis, but does not explicitly state when to use it vs alternatives like nih_spending_by_category or nih_search_projects.

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/lzinga/us-gov-open-data-mcp'

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