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Openaire

by io.github.pipeworx-io
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Search Projects

search_projects
Read-onlyIdempotent

"What EU / NIH / NSF projects are funded on [topic]" / "Horizon Europe projects on [X]" / "CORDIS lookup for [Y]" — search funded research projects (CORDIS for EC; also NSF, NIH, Wellcome Trust, others). Returns project title, funder, budget, coordinator, partners, dates. Use for funding-landscape analysis, grant precedent research.

Example tool call

This call uses example arguments supplied in the tool’s input schema.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "query": "artificial intelligence ethics"
    },
    "name": "search_projects"
  }
}

Input Schema

NameRequiredDescriptionDefault
pageNo1-based page (default 1)
sizeNoPage size, 1-100 (default 20)
queryYesFree-text query (matches title/abstract/keywords)
funderNoFunder short name
countryNoCoordinator country (ISO alpha-2)
from_yearNoEarliest project start year

Output Schema

NameRequiredDescriptionDefault
pageYesCurrent page number (1-based)
countYesNumber of results in this response
queryYesThe search query that was executed
totalYesTotal number of matching projects
resultsYesArray of project objects
page_sizeYesNumber of results per page

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • addedInput schema / examples
      Added value: +[
+  {
+    "query": "artificial intelligence ethics"
+  },
+  {
+    "country": "US",
+    "from_year": "2019",
+    "funder": "NSF",
+    "query": "renewable energy"
+  }
+]
    • changedOutput schema / (root)
      Previous value: -nullNew value: +{
+  "properties": {
+    "count": {
+      "description": "Number of results in this response",
+      "type": "number"
+    },
+    "page": {
+      "description": "Current page number (1-based)",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "page_size": {
+      "description": "Number of results per page",
+      "type": [
+        "number",
+        "null"
+      ]
+    },
+    "query": {
+      "description": "The search query that was executed",
+      "type": "string"
+    },
+    "results": {
+      "description": "Array of project objects",
+      "items": {
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "total": {
+      "description": "Total number of matching projects",
+      "type": [
+        "number",
+        "null"
+      ]
+    }
+  },
+  "required": [
+    "query",
+    "total",
+    "page",
+    "page_size",
+    "count",
+    "results"
+  ],
+  "type": "object"
+}
  2. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already indicate read-only, idempotent, non-destructive. The description adds context about the returned fields and the matching logic (title/abstract/keywords), which is helpful beyond 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?

The description is concise and front-loaded with example queries. It efficiently conveys the tool's purpose and scope, though it could be slightly tighter.

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?

Given high schema coverage and the presence of an output schema, the description is complete enough for an agent to understand the tool's purpose and usage. It covers the main aspects without needing further detail.

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 description coverage is 100%. The description includes example queries that demonstrate parameter combinations, adding semantic value beyond the schema descriptions alone.

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 searches funded research projects across multiple funders (EU, NIH, NSF). It provides example queries and a list of returned fields, distinguishing it from sibling search tools like search_datasets or search_publications.

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 includes explicit use cases ('funding-landscape analysis, grant precedent research') and example queries, but does not explicitly mention when to avoid this tool or compare to alternatives like get_project.

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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