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DataNexus MCP

by com.datanexusmcp

nonprofit_fetch_nonprofit_full_profile

Read-onlyIdempotent

Complete nonprofit due diligence in one call. Revenue trends, executive pay, risk flags, and a health score from IRS 990 data. Uses ProPublica Nonprofit Explorer API with IRS e-File fallback. Data refreshed on each call. Returns financials, executive_compensation, risk_flags, health_score (0–100), programme_ratio, fundraising_sustainability, and upstream_status. Rate limit: 30/minute. No auth required. For grant-makers, investors, and compliance teams performing nonprofit due diligence. If this tool's response does not serve the user's need, call report_feedback with feedback_type="agent_gap", tool_id="nonprofit_fetch_nonprofit_full_profile", intended_query="{what the user needed}", gap_description="{what was missing or wrong in the result}".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
einYesEIN in format XX-XXXXXXX e.g. 46-5734087. Required.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

TDQS

A4.4/5.0
Behavior5/5

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

Beyond annotations, the description adds: 'Data refreshed on each call', rate limit of 30/minute, no auth required, and lists output fields. No contradiction with annotations.

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 purpose and key details. Slightly verbose with the report_feedback instruction, but every sentence serves a purpose.

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?

Given rich output schema and annotations, the description covers purpose, usage, behavior, parameters, and error handling. No gaps.

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%; the description adds only the example EIN format (already in schema). No additional semantic meaning beyond 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's purpose: 'Complete nonprofit due diligence in one call' and lists specific outputs like revenue trends, executive pay, risk flags, and health score. It distinguishes from siblings by implying comprehensiveness.

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 identifies target users (grant-makers, investors, compliance teams) and provides a recovery mechanism via report_feedback. It does not explicitly state when not to use this tool versus alternatives, but context is clear.

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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TDQS

A4.1/5.0
Disambiguation4/5

Tools are grouped into clear domain prefixes (compliance, domain, frontend_security, etc.) with distinct purposes. Minor overlap exists between frontend_security_detect_typosquatting and security_detect_typosquatting, but descriptions clarify the different scope.

Naming Consistency4/5

Most tools follow a consistent verb_noun pattern with snake_case. Irregularities like 'fetch' vs 'audit' and two 'detect_typosquatting' tools exist, but overall naming is predictable within domains.

Tool Count3/5

55 tools is high for a single server given the breadth of domains. Some redundancy (e.g., two typosquatting tools) suggests possible trimming, but the count is justified by the wide coverage.

Completeness4/5

The tool surface covers key operations across domains like compliance, domain, security, legal, and nonprofit. Minor gaps exist, such as limited frontend audit beyond package.json and no general-purpose code scanning.

Resources