niaid-data-mcp-server
Allows querying the NIAID Data Ecosystem using Elasticsearch query syntax, supporting field-specific queries, aggregations, pagination, and sorting.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@niaid-data-mcp-server search for COVID-19 datasets"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
NIAID Data MCP Server
An MCP (Model Context Protocol) server for the NIAID Data Ecosystem API, enabling LLMs to search biomedical research resources — datasets, clinical studies, publications, repositories, and more — funded or supported by NIAID.
Tools
niaid_data_query
Search the NIAID Data Ecosystem using Elasticsearch query string syntax.
Parameters:
Parameter | Type | Default | Description |
| string |
| Elasticsearch query string. Supports field-specific queries, boolean operators, and wildcards. |
| int | 10 | Number of results to return (1–1000). |
| int | 0 | Number of results to skip (for pagination). |
| string | — | Sort field; prefix with |
| string | — | Comma-separated fields to return (e.g., |
| list[string] | — | Fields to aggregate/facet by (e.g., |
| int | 10 | Max aggregation buckets per field (1–1000). |
| bool | — | Include relevance score explanation. |
| string |
|
|
Example queries:
q="COVID-19 AND @type:Dataset"— find COVID-19 datasetsq="*", aggs=["@type"]— summarize resource types across the whole catalogq="malaria", sort="-date", size=20— most recent malaria resources
Related MCP server: Asset Library MCP Server
Setup
Requires Python 3.11+ and uv.
uv syncRunning as a stdio MCP server (for Claude Desktop / MCP clients)
uv run python main.pyClaude Desktop config (claude_desktop_config.json):
{
"mcpServers": {
"niaid-data": {
"command": "uv",
"args": ["run", "python", "main.py"],
"cwd": "/path/to/niaid-data-mcp-server"
}
}
}Running as an HTTP server
PORT=8000 uv run python main.pyA /health endpoint is available at http://localhost:8000/health.
Available Tools
3 toolsniaid_data_getGet NIAID Data Record by IDARead-onlyIdempotent
Fetch the complete record for a single NIAID Data Ecosystem resource by its ID.
Retrieves all available fields for a specific resource using its unique identifier. Use this after niaid_data_query to get the full details of a record of interest.
Args: params (GetInput): Validated input parameters containing: - id (str): Unique record identifier from the '_id' field of query results (e.g., 'dde_373d5e89c734f65e'). - response_format (ResponseFormat): 'json' (default) for the complete raw record, or 'markdown' for a human-readable summary.
Returns: str: The complete record data.
JSON response: Full record object as returned by the API, including all
available fields (name, description, author, date, url, conditionsOfAccess,
measurementTechnique, species, funding, citation, etc.).
Markdown response: Formatted summary with key fields highlighted.
Error responses:
- "Error: Record not found for ID '...'" if the ID does not exist
- "Error: <message>" for API or network failuresExamples: - Use when: "Get full details for dataset dde_373d5e89c734f65e" -> params with id='dde_373d5e89c734f65e' - Use when: After a query returns results and you need all fields for one record -> params with id=<_id from query hit>, response_format='json'
Inputs: params (required). Returns: result
niaid_data_queryQuery NIAID Data EcosystemARead-onlyIdempotent
Search the NIAID Data Ecosystem for biomedical research resources.
Queries the NIAID Data Ecosystem API (https://data.niaid.nih.gov), which indexes datasets, clinical studies, publications, and other research resources related to infectious and immune-mediated diseases funded or supported by NIAID.
Supports Elasticsearch query string syntax for powerful full-text and field-specific searches. Results include datasets, clinical trials, repositories, computational tools, and more.
Args: params (QueryInput): Validated input parameters containing: - q (str): Elasticsearch query string. Use '' for all records. Supports field-specific syntax: 'name:COVID', 'author.name:Smith', '@type:Dataset', 'conditionsOfAccess:Open'. Default: ''. - size (Optional[int]): Number of results per page (1-1000). Default: 10. - offset (Optional[int]): Results to skip for pagination. Default: 0. - sort (Optional[str]): Sort field; prefix with '-' for descending (e.g., '-date'). Default: relevance score. - fields (Optional[str]): Comma-separated fields to return (e.g., 'name,description,@type,date'). Returns all fields if omitted. - aggs (Optional[List[str]]): Fields to aggregate/facet by (e.g., ['@type', 'conditionsOfAccess']). Useful for summarizing result distributions without reading each record. - facet_size (Optional[int]): Max aggregation buckets per field. Default: 10. - explain (Optional[bool]): Include relevance score explanation. - response_format (ResponseFormat): 'markdown' (default) for readable summaries or 'json' for complete structured data.
Returns: str: Formatted search results.
Markdown response includes:
- Total result count and pagination info
- For each hit: name, type, ID, score, description (truncated), URL, date
- Aggregation summaries (if aggs requested)
JSON response schema:
{
"total": int, # Total matching records
"count": int, # Records in this response
"offset": int, # Current pagination offset
"has_more": bool, # Whether more results are available
"next_offset": int | null, # Offset for next page
"took_ms": int, # Query time in milliseconds
"hits": [...], # Full record objects from the API
"aggregations": {...} # Aggregation buckets (if requested)
}
Error response: "Error: <message with suggested fix>"Examples: - Use when: "Find open-access COVID-19 datasets" -> params with q='COVID-19 AND @type:Dataset AND conditionsOfAccess:Open' - Use when: "What types of resources are available?" -> params with q='*', aggs=['@type'], size=0 - Use when: "Find datasets with access conditions distribution" -> params with q='@type:Dataset', aggs=['conditionsOfAccess'], size=5 - Use when: "Search for malaria resources sorted by date" -> params with q='malaria', sort='-date', size=20 - Use when: "Page through results" (after first call with offset=0, size=10) -> params with same q, offset=10, size=10
Error Handling: - Returns "Error: Invalid query (HTTP 400)..." if query syntax is invalid - Returns "Error: Rate limit exceeded (HTTP 429)..." if too many requests - Returns "Error: Request timed out..." if query is too broad/slow
Inputs: params (required). Returns: result
niaid_data_summarizeSummarize NIAID Data Search ResultsARead-onlyIdempotent
Summarize a NIAID Data search without returning all records to the context.
Use this tool BEFORE niaid_data_query when a search may return many results, or when you need to understand what's available before fetching full records. Returns a compact overview: total count, distribution breakdowns across key fields, a small sample of top hits, and specific suggestions for narrowing the search.
This is the right tool when:
You don't know how many results a query will return
The user asks "what's available about X" or "give me an overview of X"
A previous niaid_data_query returned 1000+ hits
You need to help the user decide how to filter or focus their search
Args: params (SummarizeInput): Validated input parameters containing: - q (str): Elasticsearch query string (same syntax as niaid_data_query). Use '' to summarize the entire catalog. Default: ''. - sample_size (Optional[int]): Top-scoring records to show as examples (1–20). Does NOT return all results. Default: 5.
Returns: str: Markdown summary containing:
**Overview**
- Total matching records and query time
**Distribution** (fields with data only)
- Resource type breakdown (Dataset, ComputationalTool, ResourceCatalog, …)
- Access conditions (Open, Restricted, Closed)
- Health conditions, infectious agents, species, measurement techniques,
topic categories, funders — wherever data exists for this query
**Sample records** (top `sample_size` hits by relevance)
- Name, type, ID, and description snippet for each
**Refinement suggestions**
Generated from the actual distribution data:
- Concrete filter additions (e.g., `AND @type:Dataset`)
- Field-specific search tips
- Pagination guidance if proceeding with niaid_data_queryExamples: - Use when: "What COVID-19 resources are available?" -> params with q='COVID-19' - Use when: A query just returned 48,000 results -> params with q= to understand how to narrow it - Use when: "Give me an overview of malaria datasets" -> params with q='malaria' - Don't use when: You need specific records (use niaid_data_query instead) - Don't use when: You have a specific ID (use niaid_data_get instead)
Inputs: params (required). Returns: result
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
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TDQS
Scored across 3 tools
Each tool has a clearly distinct purpose: query for searching with pagination, get for retrieving a single record by ID, and summarize for overview and refinement suggestions. No overlapping functionality.
All tools follow the consistent pattern 'niaid_data_<verb>' with lowercase snake_case verbs (query, get, summarize). The naming convention is uniform and predictable.
Three tools is well-scoped for a read-only data search server. Each tool serves a necessary, non-redundant function, and the count is within the ideal range for a single API integration.
The tool set covers the complete user workflow: summarize to explore and narrow a search, query to retrieve paginated hits, and get to fetch full details for a specific record. No obvious gaps in the search-and-retrieve lifecycle.
Maintenance
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