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xiuxiansk

mcp-local-rag

by xiuxiansk

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
DB_PATHNoVector database location./lancedb/
BASE_DIRNoOne document root; default is current directory.
BASE_DIRSNoJSON array of document roots; takes precedence over BASE_DIR
CACHE_DIRNoModel cache directory./models/
RAG_DTYPENoEmbedding dtype supplied by the selected modelfp32
MODEL_NAMENoHugging Face embedding modelXenova/all-MiniLM-L6-v2
RAG_DEVICENoONNX Runtime execution devicecpu
RAG_GROUPINGNo`similar` keeps the first relevance group; `related` keeps up to two, using significant vector-distance gaps as boundaries.
MAX_FILE_SIZENoMaximum file size in bytes104857600
RAG_MAX_FILESNoLimit results to top N files (e.g., 1 for single best file).
CHUNK_MIN_LENGTHNoMinimum chunk length in characters (1–10000)50
RAG_MAX_DISTANCENoFilter out low-relevance results (e.g., 0.5).
RAG_HYBRID_WEIGHTNoKeyword boost factor (0.0–1.0). 0 disables keyword reranking; 1 applies the maximum boost.0.6

Capabilities

Features and capabilities supported by this server

CapabilityDetails
tools
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
query_documentsA

Search ingested documents with hybrid keyword + semantic matching. Returns results sorted by relevance, each with filePath, chunkIndex, text, fileTitle, score (0 = best, higher = worse), and source (for ingest_data items).

ingest_fileA

Ingest a document file (PDF, DOCX, TXT, MD) into the vector database. Path must be absolute; re-ingesting the same path replaces its existing data. Returns { filePath, chunkCount, timestamp, fileTitle }.

ingest_dataA

Ingest in-memory content as a string (use ingest_file for files on disk). The source identifier enables re-ingestion to update existing content. Returns { filePath, chunkCount, timestamp, fileTitle }.

delete_fileA

Delete a previously ingested file or data from the vector database. Use filePath for files ingested via ingest_file, or source for data ingested via ingest_data. Either filePath or source must be provided. Returns deleted (operation succeeded), removedChunks, and existed (whether anything was actually present).

list_filesA

List supported files (PDF, DOCX, TXT, MD) under the configured base directories and whether each is ingested. Returns { baseDirs, files, sources }; sources lists ingested items reported apart from the file scan, chiefly ingest_data content (web pages, clipboard, etc.).

statusA

Get index status: { documentCount, chunkCount, memoryUsage (MB), uptime (s), ftsIndexEnabled, searchMode }.

read_chunk_neighborsA

Read the chunks immediately before and after a query_documents result, in the same document, for more surrounding context. Pass chunkIndex from the result plus exactly one of filePath (ingest_file) or source (ingest_data). Returns the target chunk (isTarget: true) and its neighbors, ascending by chunkIndex; an out-of-range chunkIndex returns []. Defaults: before=2, after=2 (max 50 each).

sync_startA

Reconcile the index with the files on disk: ingest new and changed files, leave unchanged files alone, and remove index entries for files that are gone. Returns { jobId } without waiting for the run to finish; poll sync_status with that jobId for progress and the final outcome. Only one job is kept, and it is lost when the server process exits.

sync_statusA

Get the current or latest sync job record: { jobId, state ("running" | "succeeded" | "failed"), total (null until scanning has counted the files on disk), completed (upserted + skipped + empty; pruned is counted separately), summary { upserted, skipped, empty, pruned }, warnings, error (null unless the job failed) }. An unknown jobId means the job was replaced by a newer one or lost with a previous server process.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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