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Augmented-Nature

ProteinAtlas MCP Server

search_by_tissue

Find proteins with specific expression levels in human tissues using Human Protein Atlas data. Filter results by tissue type and expression level to identify relevant proteins.

Instructions

Find proteins highly expressed in specific tissues

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tissueYesTissue name (e.g., liver, brain, heart)
expressionLevelNoExpression level filter
formatNoOutput format (default: json)
maxResultsNoMaximum number of results (1-10000, default: 100)

Implementation Reference

  • The core handler function for the 'search_by_tissue' tool. Validates input using isValidTissueSearchArgs, constructs a Lucene-style search query for tissue expression, calls the searchProteins helper to query the Human Protein Atlas API, and returns formatted JSON results or an MCP error response.
    private async handleSearchByTissue(args: any) {
      if (!isValidTissueSearchArgs(args)) {
        throw new McpError(ErrorCode.InvalidParams, 'Invalid tissue search arguments');
      }
    
      try {
        let searchQuery = `tissue:"${args.tissue}"`;
        if (args.expressionLevel) {
          searchQuery += ` AND expression:"${args.expressionLevel}"`;
        }
    
        const result = await this.searchProteins(searchQuery, args.format || 'json', undefined, args.maxResults);
        return {
          content: [
            {
              type: 'text',
              text: typeof result === 'object' ? JSON.stringify(result, null, 2) : String(result),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `Error searching by tissue: ${error instanceof Error ? error.message : 'Unknown error'}`,
            },
          ],
          isError: true,
        };
      }
  • src/index.ts:496-508 (registration)
    MCP tool registration entry in the ListTools handler, defining the tool name, description, and input schema advertised to clients.
    {
      name: 'search_by_tissue',
      description: 'Find proteins highly expressed in specific tissues',
      inputSchema: {
        type: 'object',
        properties: {
          tissue: { type: 'string', description: 'Tissue name (e.g., liver, brain, heart)' },
          expressionLevel: { type: 'string', enum: ['high', 'medium', 'low', 'not detected'], description: 'Expression level filter' },
          format: { type: 'string', enum: ['json', 'tsv'], description: 'Output format (default: json)' },
          maxResults: { type: 'number', description: 'Maximum number of results (1-10000, default: 100)', minimum: 1, maximum: 10000 },
        },
        required: ['tissue'],
      },
  • src/index.ts:678-679 (registration)
    Dispatcher switch case in CallToolRequest handler that maps 'search_by_tissue' tool calls to the handleSearchByTissue method.
    case 'search_by_tissue':
      return this.handleSearchByTissue(args);
  • Runtime input validation function (type guard) that enforces the tool's input schema, used at the start of the handler.
    const isValidTissueSearchArgs = (
      args: any
    ): args is { tissue: string; expressionLevel?: string; format?: string; maxResults?: number } => {
      return (
        typeof args === 'object' &&
        args !== null &&
        typeof args.tissue === 'string' &&
        args.tissue.length > 0 &&
        (args.expressionLevel === undefined || ['high', 'medium', 'low', 'not detected'].includes(args.expressionLevel)) &&
        (args.format === undefined || ['json', 'tsv'].includes(args.format)) &&
        (args.maxResults === undefined || (typeof args.maxResults === 'number' && args.maxResults > 0 && args.maxResults <= 10000))
      );
Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It mentions 'highly expressed' but doesn't clarify what that means quantitatively, whether results are paginated, if there are rate limits, or what the output looks like beyond format options. For a search tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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?

The description is a single, efficient sentence that front-loads the core purpose without unnecessary words. It earns its place by clearly stating what the tool does, making it easy for an agent to parse quickly.

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

Completeness2/5

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

Given the complexity of a search tool with 4 parameters, no annotations, and no output schema, the description is incomplete. It doesn't address key aspects like result format details beyond 'json' or 'tsv,' how 'highly expressed' maps to parameters, or usage context relative to siblings, leaving the agent under-informed.

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?

The description adds minimal meaning beyond the input schema, which has 100% coverage. It implies filtering by 'highly expressed' but doesn't explain how this relates to the 'expressionLevel' parameter or other inputs. With high schema coverage, the baseline is 3, as the schema already documents parameters well, and the description doesn't compensate with additional insights.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Find proteins highly expressed in specific tissues.' It specifies the verb ('Find'), resource ('proteins'), and key constraint ('highly expressed in specific tissues'). However, it doesn't explicitly differentiate from sibling tools like 'get_tissue_expression' or 'search_proteins,' which might offer similar functionality.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. With many sibling tools related to tissue expression (e.g., 'get_tissue_expression,' 'get_brain_expression,' 'search_proteins'), the lack of context leaves the agent guessing about the best choice for a given scenario.

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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