MongoDB MCP Server

import { describeAccuracyTests } from "./sdk/describeAccuracyTests.js"; import { Matcher } from "./sdk/matcher.js"; import type { CallToolResult } from "@modelcontextprotocol/sdk/types.js"; function doesUnset(field: string): Matcher { return Matcher.anyOf( // { $unset: "<field>" } || { $unset: ["<field>"] } Matcher.value({ $unset: Matcher.arrayOrSingle(Matcher.value(field)) }), // { $unset: { "<field>": "" } } Matcher.value({ $unset: { [field]: "" } }) ); } const embeddingParameters = { model: "voyage-3-large", outputDimension: Matcher.anyOf( Matcher.undefined, Matcher.number((n) => n === 1024) ), outputDType: Matcher.anyOf(Matcher.undefined, Matcher.value("float")), }; describeAccuracyTests([ { prompt: "Group all the movies in 'mflix.movies' namespace by 'release_year' and give me a count of them", expectedToolCalls: [ { toolName: "aggregate", parameters: { database: "mflix", collection: "movies", pipeline: [ { $group: { _id: "$release_year", count: { $sum: 1 } } }, // For the sake of accuracy, we allow any sort order Matcher.anyOf( Matcher.undefined, Matcher.value({ $sort: Matcher.anyValue, }) ), ], }, }, ], }, { prompt: "Run a vectorSearch query on musicfy.songs on path 'title_embeddings' using the index 'titles' with the model voyage-3-large to find all 'hammer of justice' songs.", expectedToolCalls: [ { toolName: "collection-indexes", parameters: { database: "musicfy", collection: "songs", }, optional: true, }, { toolName: "aggregate", parameters: { database: "musicfy", collection: "songs", pipeline: [ { $vectorSearch: { exact: Matcher.anyOf(Matcher.undefined, Matcher.boolean(false)), index: "titles", path: "title_embeddings", queryVector: "hammer of justice", embeddingParameters, filter: Matcher.emptyObjectOrUndefined, limit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, doesUnset("title_embeddings"), ], responseBytesLimit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, ], mockedTools: { "collection-indexes": (): CallToolResult => { return { content: [ { type: "text", text: JSON.stringify({ name: "titles", type: "vectorSearch", status: "READY", queryable: true, latestDefinition: { type: "vector", path: "title_embeddings", numDimensions: 1024, quantization: "none", similarity: "euclidean", }, }), }, ], }; }, }, }, { prompt: "Run a vectorSearch query on musicfy.songs on path 'title_embeddings' using the index 'titles' with the model voyage-3-large to find all 'hammer of justice' songs. Keep the embedding field, do not remove it.", expectedToolCalls: [ { toolName: "collection-indexes", parameters: { database: "musicfy", collection: "songs", }, optional: true, }, { toolName: "aggregate", parameters: { database: "musicfy", collection: "songs", pipeline: [ { $vectorSearch: { exact: Matcher.anyOf(Matcher.undefined, Matcher.boolean(false)), index: "titles", path: "title_embeddings", queryVector: "hammer of justice", embeddingParameters, filter: Matcher.emptyObjectOrUndefined, limit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, Matcher.not(doesUnset("title_embeddings")), ], responseBytesLimit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, ], mockedTools: { "collection-indexes": (): CallToolResult => { return { content: [ { type: "text", text: JSON.stringify({ name: "titles", type: "vectorSearch", status: "READY", queryable: true, latestDefinition: { type: "vector", path: "title_embeddings", numDimensions: 1024, quantization: "none", similarity: "euclidean", }, }), }, ], }; }, }, }, { prompt: "Run an exact vectorSearch query on musicfy.songs on path 'title_embeddings' using the index 'titles' with the model voyage-3-large to find 10 'hammer of justice' songs in any order.", expectedToolCalls: [ { toolName: "collection-indexes", parameters: { database: "musicfy", collection: "songs", }, optional: true, }, { toolName: "aggregate", parameters: { database: "musicfy", collection: "songs", pipeline: [ { $vectorSearch: { exact: true, index: "titles", path: "title_embeddings", queryVector: "hammer of justice", embeddingParameters, filter: Matcher.emptyObjectOrUndefined, limit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, doesUnset("title_embeddings"), ], responseBytesLimit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, ], mockedTools: { "collection-indexes": (): CallToolResult => { return { content: [ { type: "text", text: JSON.stringify({ name: "titles", type: "vectorSearch", status: "READY", queryable: true, latestDefinition: { type: "vector", path: "title_embeddings", numDimensions: 1024, quantization: "none", similarity: "euclidean", }, }), }, ], }; }, }, }, { prompt: "Run an approximate vectorSearch query on mflix.movies on path 'plot_embeddings' with the model voyage-3-large to find all 'sci-fi' movies.", expectedToolCalls: [ { toolName: "collection-indexes", parameters: { database: "mflix", collection: "movies", }, }, { toolName: "aggregate", parameters: { database: "mflix", collection: "movies", pipeline: [ { $vectorSearch: { exact: Matcher.anyOf(Matcher.undefined, Matcher.boolean(false)), index: "my-index", path: "plot_embeddings", queryVector: "sci-fi", embeddingParameters, filter: Matcher.emptyObjectOrUndefined, limit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, doesUnset("plot_embeddings"), ], responseBytesLimit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, ], mockedTools: { "collection-indexes": (): CallToolResult => { return { content: [ { type: "text", text: JSON.stringify({ name: "my-index", type: "vectorSearch", status: "READY", queryable: true, latestDefinition: { type: "vector", path: "plot_embeddings", numDimensions: 1024, quantization: "none", similarity: "euclidean", }, }), }, ], }; }, }, }, { prompt: "(Pre-filter) Run a vectorSearch query on mflix.movies on path 'plot_embeddings' with the model voyage-3-large to find all 'sci-fi' movies. I only want movies with the `released` after 1993 (included) and are published in catalan.", expectedToolCalls: [ { toolName: "collection-indexes", parameters: { database: "mflix", collection: "movies", }, }, { toolName: "aggregate", parameters: { database: "mflix", collection: "movies", pipeline: [ { $vectorSearch: { exact: Matcher.anyOf(Matcher.undefined, Matcher.boolean(false)), index: "my-index", path: "plot_embeddings", queryVector: "sci-fi", numCandidates: Matcher.anyOf(Matcher.number(), Matcher.undefined), limit: Matcher.anyOf(Matcher.number(), Matcher.undefined), embeddingParameters, filter: { released: { $gte: 1993 }, language: Matcher.caseInsensitiveString("catalan"), }, }, }, doesUnset("plot_embeddings"), ], responseBytesLimit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, ], mockedTools: { "collection-indexes": (): CallToolResult => { return { content: [ { type: "text", text: JSON.stringify({ name: "my-index", type: "vectorSearch", status: "READY", queryable: true, latestDefinition: { fields: [ { type: "vector", path: "plot_embeddings", numDimensions: 1024, quantization: "none", similarity: "euclidean", }, { type: "filter", path: "language", }, { type: "filter", path: "released", }, ], }, }), }, ], }; }, }, }, { prompt: "(No-prefilter) Run a vectorSearch query on mflix.movies on path 'plot_embeddings' with the model voyage-3-large to find all 'sci-fi' movies. I only want movies with `released` after 1993 (included) and are published in catalan.", expectedToolCalls: [ { toolName: "collection-indexes", parameters: { database: "mflix", collection: "movies", }, }, { toolName: "aggregate", parameters: { database: "mflix", collection: "movies", pipeline: [ { $vectorSearch: { exact: Matcher.anyOf(Matcher.undefined, Matcher.boolean(false)), index: "my-index", path: "plot_embeddings", queryVector: "sci-fi", numCandidates: Matcher.anyOf(Matcher.number(), Matcher.undefined), limit: Matcher.anyOf(Matcher.number(), Matcher.undefined), embeddingParameters, filter: Matcher.emptyObjectOrUndefined, }, }, { $match: { released: { $gte: 1993 }, language: Matcher.caseInsensitiveString("catalan"), }, }, doesUnset("plot_embeddings"), ], responseBytesLimit: Matcher.anyOf(Matcher.number(), Matcher.undefined), }, }, ], mockedTools: { "collection-indexes": (): CallToolResult => { return { content: [ { type: "text", text: JSON.stringify({ name: "my-index", type: "vectorSearch", status: "READY", queryable: true, latestDefinition: { fields: [ { type: "vector", path: "plot_embeddings", numDimensions: 1024, quantization: "none", similarity: "euclidean", }, ], }, }), }, ], }; }, }, }, ]);