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get_protein_features

Retrieve functional features and domains for a protein using its UniProt accession number to analyze protein structure and biological roles.

Instructions

Get functional features and domains for a protein

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
accessionYesUniProt accession number

Implementation Reference

  • The handler function for 'get_protein_features' tool. Fetches protein data from UniProt API and extracts specific features like domains, active sites, binding sites, comments, and keywords.
    private async handleGetProteinFeatures(args: any) {
      if (!isValidProteinInfoArgs(args)) {
        throw new McpError(ErrorCode.InvalidParams, 'Invalid protein features arguments');
      }
    
      try {
        const response = await this.apiClient.get(`/uniprotkb/${args.accession}`, {
          params: { format: 'json' },
        });
    
        // Extract features and domains from the response
        const protein = response.data;
        const features = {
          accession: protein.primaryAccession,
          name: protein.uniProtkbId,
          features: protein.features || [],
          comments: protein.comments || [],
          keywords: protein.keywords || [],
          domains: protein.features?.filter((f: any) => f.type === 'Domain') || [],
          activeSites: protein.features?.filter((f: any) => f.type === 'Active site') || [],
          bindingSites: protein.features?.filter((f: any) => f.type === 'Binding site') || [],
        };
    
        return {
          content: [
            {
              type: 'text',
              text: JSON.stringify(features, null, 2),
            },
          ],
        };
      } catch (error) {
        return {
          content: [
            {
              type: 'text',
              text: `Error fetching protein features: ${error instanceof Error ? error.message : 'Unknown error'}`,
            },
          ],
          isError: true,
        };
      }
    }
  • src/index.ts:737-737 (registration)
    Tool dispatch/registration in the CallToolRequestSchema switch statement.
    return this.handleGetProteinFeatures(args);
  • Tool schema and metadata registration in the ListToolsRequestSchema response.
    name: 'get_protein_features',
    description: 'Get functional features and domains for a protein',
    inputSchema: {
      type: 'object',
      properties: {
        accession: { type: 'string', description: 'UniProt accession number' },
      },
      required: ['accession'],
    },
  • Validation helper function used by get_protein_features to validate input arguments.
    const isValidProteinInfoArgs = (
      args: any
    ): args is { accession: string; format?: string } => {
      return (
        typeof args === 'object' &&
        args !== null &&
        typeof args.accession === 'string' &&
        args.accession.length > 0 &&
        (args.format === undefined || ['json', 'tsv', 'fasta', 'xml'].includes(args.format))
      );
    };
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 'Get functional features and domains' but does not specify whether this is a read-only operation, if it requires authentication, what the output format is, or any rate limits. For a 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 directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy 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 lack of annotations and output schema, the description is incomplete for a tool that likely returns complex data (functional features and domains). It does not explain what 'features and domains' entail, the format of the response, or any limitations, leaving the agent with insufficient context for effective use.

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 input schema has 100% description coverage, with the single parameter 'accession' clearly documented as a 'UniProt accession number'. The description does not add any additional meaning beyond this, such as examples or constraints, so it meets the baseline of 3 where the schema does the heavy lifting.

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 action ('Get') and target ('functional features and domains for a protein'), making the purpose understandable. However, it does not explicitly differentiate this tool from sibling tools like 'get_protein_domains_detailed' or 'get_protein_info', which might offer overlapping or related functionality, preventing a score of 5.

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, such as sibling tools like 'get_protein_domains_detailed' or 'get_protein_info'. It lacks context on prerequisites, exclusions, or specific use cases, leaving the agent to infer usage from the tool name alone.

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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