MCP server for advanced web search using Tavily
Nothing to run from here
Local Rag is installed from its publisher's own source and answers where it runs, so this marketplace is not in the path of a single call. There is no address here to send one to, and a panel that pretended otherwise would be showing you an answer we made up. Install it and call it from your own client — the Installation tab has the entry for each one.
99/100
trust score
7
downloads a day
local
runs on your machine
382
downloads in 30d
What it does
Semantic code & doc search with keyword boost. AST code nav, auto HF mirror, local, privacy-first.
Quickstart
# 1 — add it to Claude Code
claude mcp add --scope user damoqiongqiu-local-rag-mcp '--' npx -y @damoqiongqiu/mcp-local-rag
Local Rag costs nothing on mcprush: there is no plan to choose here, no cap to set and nothing mcprush can bill you for.
Publishernot claimed
DAAll 2 servers
damoqiongqiu2 servers
2 categories
Collected from a public index. Nobody has claimed this account, so nothing here was written by its author — claim it if it is yours.
Installation
Where are you running it?
Every route below installs the same thing and ends at the same approval screen. This one runs on your machine: your client starts Local Rag as a process under your own user, with your files and your network, so the tool surface below is what it can do to your computer rather than to a server somewhere else. Its scan result is on the Security tab — read the surface before you approve it.
Claude Codedeclared by this listing
This is a public server: you run it yourself and this marketplace is not in the path. You need Node.js — the current LTS (24) is the safe choice; npx comes with it. Claude Code registers it in one command; --scope user makes it available in every project. The '--' is in quotes so that PowerShell passes it on.
claude mcp add --scope user damoqiongqiu-local-rag-mcp '--' npx -y @damoqiongqiu/mcp-local-ragReconnect, or start a new session, and the tools appear in the model’s tool list.
Free on mcprush, and it runs from its publisher’s own package: this marketplace is not in the path, so there is no key of ours to hold and no card to add.
What it asks of you
Nothing is required, but it can take 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/)), 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), 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 s), 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 th), CHUNK_MIN_LENGTH (Minimum chunk length in characters (1-10000, defaults to 50). Chunks shorter than this threshold are filtered out during ingestion.), 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), 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, ..), 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 th), RAG_WATCH (Enable automatic file watcher to detect changes and re-index modified files (true/1 to enable). Useful during active development.), HF_ENDPOINT (Explicit HuggingFace endpoint URL to use for model downloads. When set, auto-mirror detection is skipped and this URL is used directly. Useful when you have a f), HF_AUTO_MIRROR (Enable automatic mirror detection for HuggingFace downloads (defaults to true). Set to "false" or "0" to disable and use huggingface.co directly. The mirror cha), HTTPS_PROXY (HTTPS proxy URL for downloading embedding models (e.g. http://proxy:8080). Required only if behind a corporate proxy.), HTTP_PROXY (HTTP proxy URL for downloading embedding models. Fallback if HTTPS_PROXY is not set.) if you want to set them.
What it writes
One config entry your client uses to start the process locally. A local server runs with your file system and your network, which is why it is priced without metering.
What you approve
This listing has not published its tool surface here yet, so what a client will ask you to approve is whatever the manifest declares at install time.
Tool surface
What the model actually sees. Descriptions are diffed on every release — see version history.
No tool surface on file
This listing has not published its tool list here yet. Nothing is shown here rather than another listing’s tools, which is what this page used to do.
Free
$0 forever
- Every tool, no call limit
- No card, and mcprush charges nothing for it
- Source published under MIT
- Runs on your machine — nothing of it reaches our gateway
- Nothing to cap, because mcprush bills nothing
What counts against your monthly calls
| Tool | Unit | Calls used | Out of the allowance |
|---|
Nothing here is billable: mcprush charges nothing to install Local Rag or to call it, at any volume.
Call allowance · this installenforced at the gateway
Monthly allowance, in calls
—
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Alert at 80% · then the tool returns a normal MCP error
Used this month: —
ATrust score 99 / 100
Release 0.21.0 · scanned 14 Oct 2026
Two independent axes, because powerful and malicious are different questions. The grade is threat only. The capability level is blast radius, and it is never a penalty on the grade — it is priced as one subtract-only term in the score, where you can see it.
Threat score100
Client score99
Findings0 threat · 0 capability
Capabilityminimal
Coveragesource
Verificationrepo
Surface digestc6f65fdd0799d9b362bc602377842781efced8de4c81561f9867b8f517ea4162
Score vectorthreat 100 → client 99
| Term | Level | What it prices | Points |
|---|---|---|---|
| capability-exposure | minimal | capability blast radius (minimal) — client exposure if the model is manipulated | −0 |
| verification-discount | repo | publisher verification (public source) — no provenance, but the source is public and inspectable | −1 |
| coverage-honesty | source | inspection depth (source) — how much of the target the scan could see | −0 |
score = clamp(round(threatScore − E_cap − E_ver − E_cov), 0, 100). No model, no opinion, no network call at scoring time: the same methodology version against the same bytes always produces this number, and every line above is a field of the report rather than a summary of it.
What the scan could actually read
A grade is only as meaningful as its coverage, so the scanner publishes its own depth before it publishes its result.
Tool surfacenot available
Implementation sourceread
Package metadataread
Live transportnot available
No tools were enumerated, so prompt-injection, capability and toxic-flow analysis had no tool surface to inspect. To grade a package’s real runtime tools, scan the running server: --command "npx -y <package>".
Capability — what it could do if the model were manipulated
Tags derived from each tool’s schema and the implementation, not from what the tool calls itself. minimal is the level these add up to.
| Tool | Capability tags | Why the tag was assigned |
|---|---|---|
| No per-tool rows for this release — see the note below. | ||
No tool surface was enumerated, so there is nothing to attribute a capability to.
Toxic-flow graph
The lethal trifecta, checked as a graph rather than as a checklist: untrusted input, a sensitive source and an external sink have to meet before there is a path worth worrying about.
The public result for this release does not print the flow graph, so there is nothing to show here. That is not the same as "no paths were found": what the scan did read is above, under coverage.
Supply chain and provenance
Integrityfirst-seen
Surface digestc6f65fdd0799d9b3
Scanned2026-10-14
This is the first scan of this surface here, so there is nothing yet to compare it against.
Every result on this tab comes from one deterministic pass over the published package — offline, rule by rule, and auditable line by line above. Same methodology version, same bytes, same score.
Release history
Always latest — the install command names no version, so it installs the newest release when it runs; the current release on file is 0.21.0. Pin a release below and the command asks for exactly that one.
0.21.0
undated
latestNo release note was published with this version.
—
no reviews yet
Who can review
One review per account, from a signed-in account that does not publish this listing. Nothing else is asked — you can say what you think before you install it. Publishers can reply once per review, and a review can be edited or deleted by whoever wrote it.
Sign in to write one
Any signed-in account that does not publish Local Rag can review it, once — before installing it or after. A review from an account that has installed it is marked as one.
No reviews yet
Nobody has reviewed this listing. The rating on the card is the mean of the reviews written here and nothing else, so there is no rating until somebody writes the first — which takes a signed-in account that does not publish it, and nothing else.