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hybridSearch

Combine keyword and semantic search to find content by balancing exact matches with contextual relevance in knowledge bases.

Instructions

Performs a combined keyword and semantic search, balancing between exact matches and semantic similarity. Requires hybridConfig with weights for both search types.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
namespaceIdNo
queryYes
topKNo
scoreThresholdNo
filterNo
hybridConfigYes
tenantIdNo
searchTypeNo

Implementation Reference

  • MCP server tool handler for 'hybridSearch'. Extracts parameters, creates SourceSyncApiClient using createClient, calls its hybridSearch method with appropriate defaults, wrapped in safeApiCall for error handling.
    async (params: any) => {
      return safeApiCall(async () => {
        const {
          namespaceId,
          query,
          topK,
          scoreThreshold,
          filter,
          hybridConfig,
          tenantId,
          searchType,
        } = params
    
        // Create a client with the provided parameters
        const client = createClient({ namespaceId, tenantId })
    
        // Call the hybridSearch method with the searchType (default to HYBRID if not provided)
        return await client.hybridSearch({
          query,
          topK,
          scoreThreshold,
          filter,
          hybridConfig,
          searchType: searchType || SourceSyncSearchType.HYBRID,
        })
      })
    },
  • Zod schema defining the input parameters for the hybridSearch tool, including query, optional topK, scoreThreshold, filter, required hybridConfig with weights, optional namespaceId and searchType, and tenantId.
    export const HybridSearchSchema = z.object({
      namespaceId: namespaceIdSchema.optional(),
      query: z.string(),
      topK: z.number().optional(),
      scoreThreshold: z.number().optional(),
      filter: z
        .object({
          metadata: z.record(z.union([z.string(), z.array(z.string())])).optional(),
        })
        .optional(),
      hybridConfig: z.object({
        semanticWeight: z.number(),
        keywordWeight: z.number(),
      }),
      tenantId: tenantIdSchema,
      searchType: SearchTypeEnum.optional(),
    })
  • src/index.ts:602-633 (registration)
    Registration of the 'hybridSearch' MCP tool using server.tool(), specifying the tool name, description, input schema, and handler function.
    server.tool(
      'hybridSearch',
      'Performs a combined keyword and semantic search, balancing between exact matches and semantic similarity. Requires hybridConfig with weights for both search types.',
      HybridSearchSchema.shape,
      async (params: any) => {
        return safeApiCall(async () => {
          const {
            namespaceId,
            query,
            topK,
            scoreThreshold,
            filter,
            hybridConfig,
            tenantId,
            searchType,
          } = params
    
          // Create a client with the provided parameters
          const client = createClient({ namespaceId, tenantId })
    
          // Call the hybridSearch method with the searchType (default to HYBRID if not provided)
          return await client.hybridSearch({
            query,
            topK,
            scoreThreshold,
            filter,
            hybridConfig,
            searchType: searchType || SourceSyncSearchType.HYBRID,
          })
        })
      },
    )
  • Underlying implementation of hybridSearch in SourceSyncApiClient class. Sends a POST request to the /v1/search/hybrid API endpoint with the search parameters and namespaceId, returning the search response.
    public async hybridSearch({
      query,
      topK,
      scoreThreshold,
      filter,
      hybridConfig,
      searchType,
    }: Omit<
      SourceSyncHybridSearchRequest,
      'namespaceId'
    >): Promise<SourceSyncSearchResponse> {
      return this.client
        .url('/v1/search/hybrid')
        .json({
          query,
          namespaceId: this.namespaceId,
          topK,
          scoreThreshold,
          filter,
          hybridConfig,
          searchType,
        } satisfies SourceSyncHybridSearchRequest)
        .post()
        .json<SourceSyncSearchResponse>()
    }
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the requirement for hybridConfig but doesn't describe the search behavior in detail (e.g., how results are returned, pagination, rate limits, or authentication needs). The phrase 'balancing between exact matches and semantic similarity' hints at behavior but lacks specificity.

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 with two sentences that are front-loaded: the first states the purpose, and the second adds a requirement. There's no unnecessary fluff, though it could be more informative without sacrificing brevity.

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 (8 parameters, nested objects, no output schema, and no annotations), the description is incomplete. It lacks details on parameter usage, behavioral traits, and output format, making it insufficient for an AI agent to effectively invoke this tool without additional context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters2/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate for all 8 parameters. It only mentions 'hybridConfig with weights for both search types', which partially explains one parameter. Other parameters like namespaceId, query, topK, scoreThreshold, filter, tenantId, and searchType are not addressed, leaving significant gaps in understanding.

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: 'Performs a combined keyword and semantic search, balancing between exact matches and semantic similarity.' It specifies the verb ('performs'), resource ('search'), and method ('combined keyword and semantic'), though it doesn't explicitly differentiate from sibling 'semanticSearch' beyond mentioning the hybrid nature.

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 minimal guidance: it mentions that hybridConfig is required but doesn't explain when to use this tool versus alternatives like 'semanticSearch' or 'fetchDocuments'. No context on appropriate use cases, prerequisites, or exclusions is given.

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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