mcp

type AskInput struct {
	Collections    []string `` /* 130-byte string literal not displayed */
	Question       string   `json:"question" jsonschema:"the question to answer using only these collections"`
	K              int      `json:"k,omitempty" jsonschema:"number of chunks to ground on (default 8)"`
	Budget         int      `json:"budget,omitempty" jsonschema:"cap the grounding to roughly this many tokens, trimming within k (0 = no cap)"`
	Rerank         bool     `` /* 162-byte string literal not displayed */
	Hybrid         bool     `json:"hybrid,omitempty" jsonschema:"fuse BM25 keyword search with vector search (recovers exact-term and identifier matches)"`
	MMR            bool     `json:"mmr,omitempty" jsonschema:"diversify grounding with Maximal Marginal Relevance (single-collection; not with rerank)"`
	Recency        bool     `json:"recency,omitempty" jsonschema:"prefer recently-updated documents via a time decay (not with rerank/mmr)"`
	Where          []string `` /* 136-byte string literal not displayed */
	SourceGlob     string   `json:"source_glob,omitempty" jsonschema:"restrict grounding to documents whose source matches this glob, e.g. '*.pdf'"`
	Strict         bool     `json:"strict,omitempty" jsonschema:"when true, return an error instead of an ungrounded answer if no chunks match"`
	IncludeSources *bool    `json:"include_sources,omitempty" jsonschema:"include each cited chunk's full text in the citations (default true)"`
}

type AskOutput struct {
	Answer    string     `json:"answer" jsonschema:"the synthesized answer; inline [n] markers reference the citations"`
	Citations []Citation `json:"citations" jsonschema:"the chunks the answer cites, in [n] order"`
	Grounded  bool       `json:"grounded" jsonschema:"false means nothing matched and the answer rests on model knowledge alone"`
}

type Chunk struct {
	ChunkID     string `json:"chunk_id" jsonschema:"the chunk's ID"`
	Seq         int    `json:"seq" jsonschema:"the chunk's position within its document"`
	HeadingPath string `json:"heading_path,omitempty" jsonschema:"the document section the chunk came from (structure-aware chunkers only)"`
	Text        string `json:"text" jsonschema:"the chunk's stored text"`
}

type Citation struct {
	Ordinal    int    `json:"ordinal" jsonschema:"the [n] marker this citation has in the answer text"`
	Source     string `json:"source" jsonschema:"source URI of the cited document"`
	Seq        int    `json:"seq" jsonschema:"the chunk's position within its document"`
	ChunkID    string `json:"chunk_id" jsonschema:"the cited chunk's ID; pass to get_chunks to fetch it"`
	Collection string `json:"collection,omitempty" jsonschema:"origin collection (set only for multi-collection answers)"`
	Text       string `json:"text,omitempty" jsonschema:"the cited chunk's text (present when include_sources is true)"`
}

type CollectionInfo struct {
	Name       string `json:"name" jsonschema:"the collection name"`
	Model      string `json:"model" jsonschema:"the embedding model the collection is pinned to"`
	Dimensions int    `json:"dimensions" jsonschema:"the embedding dimensionality"`
	Documents  int    `json:"documents" jsonschema:"number of documents ingested"`
	Chunker    string `json:"chunker" jsonschema:"the pinned chunker spec"`
}

type CollectionStatusInput struct {
	Collection string `json:"collection" jsonschema:"the collection to inspect"`
}

type CollectionStatusOutput struct {
	Name       string `json:"name" jsonschema:"the collection name"`
	Model      string `json:"model" jsonschema:"the embedding model the collection is pinned to"`
	Dimensions int    `json:"dimensions" jsonschema:"the embedding dimensionality"`
	Documents  int    `json:"documents" jsonschema:"number of documents ingested"`
	Chunks     int    `json:"chunks" jsonschema:"number of indexed chunks"`
	Chunker    string `json:"chunker" jsonschema:"the pinned chunker spec"`
	// LastIngestAt is the most recent document ingestion time (RFC3339); it
	// advances on any re-ingest, unlike a collection's birth timestamp. Empty
	// for a collection with no documents.
	LastIngestAt string `json:"last_ingest_at,omitempty" jsonschema:"timestamp of the most recently ingested document; advances on any re-ingest"`
	// CorpusDigest is the corpus content identity (hex sha256 over the document
	// set); it changes on any add, removal, or edit and is the stable handle for
	// a provenance snapshot.
	CorpusDigest string `json:"corpus_digest" jsonschema:"content digest of the document set; changes on any add, removal, or edit"`
}

type Config struct {
	// Collections restricts which collections the tools expose, as exact names or
	// globs (path.Match against the collection name). Empty exposes all local
	// collections.
	Collections []string
	// Version is reported to clients in the MCP initialize handshake.
	Version string
}

type Deps struct {
	Catalog *app.Catalog
	Query   *app.Querier
	Ask     *app.Asker
	// Retriever composes retrieval (hybrid/rerank/mmr/recency/where/cap) for the
	// ask/query tools — the same use case the CLI and eval use.
	Retriever *app.Retriever
	// Rerank is nil when no rerank provider is configured; the ask/query tools
	// return a tool error if rerank is requested in that case (mirroring the CLI).
	Rerank *app.Reranker
	// Tokens backs the ask tool's budget trimming.
	Tokens app.TokenCounter
	// Index backs collection_status's chunk count (read-only; Entries).
	Index app.VectorIndex
}

type GetChunksInput struct {
	Collection string   `json:"collection" jsonschema:"the lore collection the chunks belong to"`
	ChunkIDs   []string `json:"chunk_ids" jsonschema:"the chunk IDs to fetch; unknown IDs are omitted from the result"`
}

type GetChunksOutput struct {
	Chunks []Chunk `json:"chunks" jsonschema:"the found chunks, in request order; absent IDs are omitted"`
}

type Hit struct {
	Text        string   `json:"text" jsonschema:"the chunk's text"`
	Source      string   `json:"source" jsonschema:"source URI of the chunk's document"`
	Score       float64  `json:"score" jsonschema:"vector similarity score (higher is more similar)"`
	ChunkID     string   `json:"chunk_id" jsonschema:"the chunk's ID; pass to get_chunks to fetch it again"`
	Seq         int      `json:"seq" jsonschema:"the chunk's position within its document"`
	Collection  string   `json:"collection,omitempty" jsonschema:"origin collection (set only for multi-collection queries)"`
	RerankScore *float64 `json:"rerank_score,omitempty" jsonschema:"cross-encoder relevance score (present only when rerank was used)"`
}

type ListCollectionsInput struct{}

type ListCollectionsOutput struct {
	Collections []CollectionInfo `json:"collections" jsonschema:"the collections this server exposes"`
}

type QueryInput struct {
	Collections []string `json:"collections" jsonschema:"the lore collection name(s) to search; at least one, all sharing one embedding space"`
	Query       string   `json:"query" jsonschema:"the search text"`
	K           int      `json:"k,omitempty" jsonschema:"number of chunks to return (default 8)"`
	SourceGlob  string   `json:"source_glob,omitempty" jsonschema:"restrict to documents whose source matches this glob, e.g. '*.pdf'"`
	Rerank      bool     `` /* 162-byte string literal not displayed */
	Hybrid      bool     `json:"hybrid,omitempty" jsonschema:"fuse BM25 keyword search with vector search (recovers exact-term and identifier matches)"`
	MMR         bool     `json:"mmr,omitempty" jsonschema:"diversify results with Maximal Marginal Relevance (single-collection; not with rerank)"`
	Recency     bool     `json:"recency,omitempty" jsonschema:"prefer recently-updated documents via a time decay (not with rerank/mmr)"`
	Where       []string `` /* 126-byte string literal not displayed */
}

type QueryOutput struct {
	Hits []Hit `json:"hits" jsonschema:"the matching chunks, best first"`
}

type Server struct {
	// contains filtered or unexported fields
}