io.github.shinpr/mcp-local-rag (io.github.shinpr/mcp-local-rag@0.18.5)

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Easy-to-setup local RAG server with minimal configuration

The current version, v0.18.5, was published to the official MCP registry on 2026-09-15. It is distributed as mcp-local-rag on npm, filed under Memory & RAG by this index, and declares 15 environment variables. Removals and unreachable sources are measured across every server this index tracks, contract drift across the servers that answer in consecutive snapshots; the index's current counts put this record in context.

Using io.github.shinpr/mcp-local-rag in Claude, Cursor, Gemini CLI, Cline, or Zed? #

MCP tool contracts can change remotely with no version bump. The mcpindex gate pins each contract and HOLDs the call when it drifts-before your agent acts. Zero credentials. This is not the package install for this server itself (use Install this server for that).

Rewrites your MCP host config so each server launches behind the gate. Inspect first: curl -fsSL https://mcpindex.ai/install.sh | less

uv tool install mcpindex-gate && mcpindex-config-wire

method

Semantic screen found no manipulation pattern in the description. Conformance probe not yet run.

mcpindex.integrity.description passINFO evidence“No malicious instructions found”via static_description

• • Semantic screen only - the deterministic conformance probe has not run on this server
• • Confidence is reported but not yet calibrated (v1)
• • Screen reads the tool description, not the live behavior
• • advisory
• • registry description only no input schema
• • screen model 8b
• • Still current: the description we screened is unchanged, re-checked against the registry
• • The registry listing (version, packages, links) changed after this screen ran - the description we assessed did not

Semantic screen: an LLM judge reads the tool description for hidden instructions (status PARTIAL). A pass means the description is not lying, not that the tool is safe: a high-capability tool with an honest description still warrants caution. The deterministic conformance probe has not been run on this server yet, so the screen here is semantic-only. Posture: advisory. Confidences are reported but not yet calibrated (calibrated=false at v1). Full verdict history is not shown on this page.

Own this server? Screen its description →

That verdict was true at screening time (snapshot 2026-09-15). #

Contracts can change after screening, with no version bump. The gate pins io.github.shinpr/mcp-local-rag’s tool contracts on first sight and holds any silent change before your agent acts - the check that keeps being true on Tuesday.

See your first HOLD in 2 minutes →

Related: how to trust an MCP server · screen before install · silent contract drift

People vet a server before wiring it in. One line on your project site or docs answers that with an independent record: screening verdict, registry provenance, contract drift history. It stays current as new screens and drift events land.

[Independent trust record for io.github.shinpr/mcp-local-rag](https://mcpindex.ai/server/io-github-shinpr-mcp-local-rag) - screening verdict, registry provenance, and contract drift monitoring.
<a href="https://mcpindex.ai/server/io-github-shinpr-mcp-local-rag">Independent trust record for io.github.shinpr/mcp-local-rag</a> - screening verdict, registry provenance, and contract drift monitoring.

A live verdict badge for your README or listing. It reflects the current screen, links back here, and updates when the verdict does.

[![mcpindex](https://mcpindex.ai/api/v1/badge/io-github-shinpr-mcp-local-rag)](https://mcpindex.ai/server/io-github-shinpr-mcp-local-rag)
<a href="https://mcpindex.ai/server/io-github-shinpr-mcp-local-rag"><img src="https://mcpindex.ai/api/v1/badge/io-github-shinpr-mcp-local-rag" alt="mcpindex verdict" height="20" /></a>

BASE_DIR Base directory for document storage (defaults to current working directory). Ignored when BASE_DIRS is set.

BASE_DIRS JSON array of base directories (e.g. '["/a","/b"]'). Takes precedence over BASE_DIR.

DB_PATH Path to LanceDB database directory (defaults to ./lancedb/)

CACHE_DIR Directory where Transformers.js models are cached (defaults to ./models/)

HF_ENDPOINT Hugging Face model download endpoint. Set this to a mirror URL when direct downloads are blocked (defaults to https://huggingface.co).

MODEL_NAME Embedding model name (defaults to Xenova/all-MiniLM-L6-v2)

MAX_FILE_SIZE Maximum file size in bytes (defaults to 104857600 / 100MB)

RAG_MAX_DISTANCE Maximum distance threshold for filtering search results. Results with distance greater than this value will be excluded. Lower values mean stricter filtering (e.g., 0.5 for high relevance only)

RAG_GROUPING Grouping mode for quality filtering. 'similar' returns only the most similar group (stops at first distance jump). 'related' includes related groups (stops at second distance jump). Unset means no grouping filter

RAG_MAX_FILES Maximum number of files to keep in search results. Results are filtered to include only chunks from the top N best-scoring files. For example, 1 returns only the single best-matching file's chunks. Unset means no file filtering.

CHUNK_MIN_LENGTH Minimum chunk length in characters (1-10000, defaults to 50). Chunks shorter than this threshold are filtered out during ingestion.

STORE_IMAGES Store supported PDF and DOCX images during ingestion and return them with matched chunks (defaults to false).

RAG_DEVICE Execution device for the embedder (defaults to cpu). Passed straight to ONNX Runtime; see the Transformers.js device source for the supported backend names. If the requested device fails to initialize, the server throws an error.

RAG_DTYPE Embedding quantization dtype for the embedder (defaults to fp32). Opt-in and pass-through; accepts any dtype the chosen model provides (fp32, fp16, q8, int8, ...). If the model has no variant for the requested dtype, the server throws an error. Changing this changes the embedding space — re-ingest existing data.

RAG_HYBRID_WEIGHT Keyword boost factor for hybrid search (0.0-1.0, defaults to 0.6). 0 means semantic similarity only; higher values increase the keyword-match contribution to the final score.

methodology

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