# mcpsurfr (pypi · mcpsurfr)

Local web search with multi-engine deep research and on-device re-ranking. No API keys.

- Trust score: 55/100 (low)
- Change this week: 0
- Registry status: active
- Liveness: live
- Owner verified: no
- Last scored: 2026-11-05

## Components

- oci · `ghcr.io/nkapila6/mcpsurfr`: 38/100, [markdown](https://verifymcp.io/servers/nkapila6-mcpsurfr/ghcr-io-nkapila6-mcpsurfr.md), [page](https://verifymcp.io/servers/nkapila6-mcpsurfr/ghcr-io-nkapila6-mcpsurfr)
- pypi · `mcpsurfr`: 55/100 (this document), [markdown](https://verifymcp.io/servers/nkapila6-mcpsurfr/mcpsurfr.md), [page](https://verifymcp.io/servers/nkapila6-mcpsurfr/mcpsurfr)

## Channel facts

- Registry: `pypi`
- Package: `mcpsurfr`
- Version: `1.2.3`
- Transport: `stdio`

## Trust breakdown

How this component scores in each security and reliability category. Every signal is checked automatically from public evidence about the published package, including repeated runs of it in an isolated sandbox, and we only credit what we can confirm. Scores are 0–100 per category. Scoring method: https://verifymcp.io/docs/scoring (what has changed: https://verifymcp.io/docs/scoring/changelog)

Scored 2026-11-05.

- **Supply Chain Security**: 50/100
  - Malware scan not yet available for this package.
  - No known CVEs affecting this package version or its production dependencies.
  - Runs hatchling.build at install time, a recognised build step with no custom scripting around it.
  - 1 of 21 dependencies flagged as unhealthy.
- **Provenance & Transparency**: 45/100
  - Source repository is publicly reachable at the declared URL.
  - Provenance check failed: no build-provenance attestation is published.
  - Clear OSI-approved license (MIT).
  - Actively maintained (last published 6 days ago).
  - Disclosure check failed: no security disclosure policy was found in the source repository.
- **Schema Quality & AI Usability**: 74/100
  - 100% of prompts and resources have a non-trivial description (not blank, and not just the item's name).
  - AI-judged instruction clarity (good).
  - Context-footprint check failed: tool/resource definitions use about 1715 tokens (~285/item across 6 items; 4 tools + 2 resources), over budget; trim descriptions and params.
  - Usage-examples check failed: none of the tools include examples.
- **Stability & Change Management**: 0/100
  - Stability not yet verified: not enough scan history yet (needs a 30-day window).
- **Tool Coverage**: 100/100
  - 100% of tools have a non-trivial description (not blank, and not just the tool's name).
  - 100% of tool parameters carry a description.
  - Structured output schemas are declared (100% of tools); any adoption earns full credit.
- **Tool Safety**: 100/100
  - No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.
  - We read all 4 captured tool definition(s), and no name or description among them implies an irreversible operation.
  - An AI judge read all 6 captured unit(s) of tool text and found none that tries to manipulate the model reading it.
- **Capabilities**: 100/100
  - Implements a current MCP spec version (2026-07-28).

**Unverified: 1 category.** A category scored 0 because we could not verify it: a data source with nothing on this package, evidence we could not reach, or a check we could not run. We only credit what we can confirm.

## Install

### How do I install the mcpsurfr MCP server?

mcpsurfr runs locally as a PyPI package, launched with uvx mcpsurfr. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.

### Claude

```bash
claude mcp add nkapila6-mcpsurfr -- uvx mcpsurfr
```

### Cursor

```json
{
  "mcpServers": {
    "nkapila6-mcpsurfr": {
      "command": "uvx",
      "args": [
        "mcpsurfr"
      ]
    }
  }
}
```

### VS Code

```json
{
  "servers": {
    "nkapila6-mcpsurfr": {
      "command": "uvx",
      "args": [
        "mcpsurfr"
      ]
    }
  }
}
```

### Codex

```bash
codex mcp add nkapila6-mcpsurfr -- uvx mcpsurfr
```

### opencode

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "nkapila6-mcpsurfr": {
      "type": "local",
      "command": [
        "uvx",
        "mcpsurfr"
      ],
      "enabled": true
    }
  }
}
```

### OpenClaw

```bash
openclaw mcp add nkapila6-mcpsurfr --command uvx --arg mcpsurfr
```

### Hermes

```yaml
mcp_servers:
  nkapila6-mcpsurfr:
    command: "uvx"
    args: ["mcpsurfr"]
```

### Netclaw

```json
{
  "McpServers": {
    "nkapila6-mcpsurfr": {
      "Transport": "stdio",
      "Command": "uvx",
      "Arguments": [
        "mcpsurfr"
      ]
    }
  }
}
```

### Vellum

```bash
assistant mcp add nkapila6-mcpsurfr -t stdio -c uvx -a mcpsurfr
```

### Other

```json
{
  "mcpServers": {
    "nkapila6-mcpsurfr": {
      "command": "uvx",
      "args": [
        "mcpsurfr"
      ]
    }
  }
}
```

## Changelog

Every change recorded for this component, newest first. Days that predate change tracking, or that we cannot explain, say so: "we were watching and nothing happened" and "we were not watching" are different claims.

### 2026-11-03 (score 55, −15)

- [security regression] Malware scan: pass → unverified

### 2026-10-30 (score 70, +15)

- [security improvement] Malware scan: unverified → pass

### 2026-10-29 (score 55)

First indexed and scored.

## MCP tools (4)

### `rag_search_ddgs` (~355 tokens)

Web search

Search the web and return the most relevant pages as text, for when whole pages are
wanted (search returns only the relevant passages). Results are re-ranked locally by
semantic similarity to the query before the top pages are fetched.

Input parameters:

- `backend` (string): Search backend, same names as deep_research. Default "auto" (ddgs            metasearch over several engines, skipping blocked ones). Non-auto            backends that return nothing are retried with…
- `exclude_domains`: Never results from these sites. Example: ["pinterest.com"]
- `include_domains`: Only results from these sites, subdomains included. Example: ["python.org", "stackoverflow.com"]
- `include_urls` (boolean): Whether to include each page's source URL for citation.                 Default: True
- `news` (boolean): Search news articles instead of the web. Results then carry their published "date". News backends: auto, bing, duckduckgo, yahoo. Pair with recency for current events.
- `num_results` (integer): Number of initial search results to rank.               More results provide better coverage but increase processing time.               Default: 10
- `query` (string, required): The search query. Use natural language questions or keywords.         Example: "latest developments in quantum computing"
- `recency`: Only results from the past "day", "week", "month" or "year".
- `region`: Region-language code like "us-en", "uk-en" or "de-de". Default: ddgs's own (us-en).
- `top_k` (integer): Number of top-ranked pages to fetch and return.         Default: 5

### `search` (~427 tokens)

Search (passages)

Search the web and return only the passages that answer the query, not whole
pages: usually about a tenth of the text of rag_search_ddgs. Use this first.

Tiers, cheapest first:
1\. Search, then keep the top_pages results whose title/snippet match best.
2\. Fetch those pages, split them into ~600-char passages, keyword-match them (BM25)
   against the query plus `keywords`.
3\. Only if that leaves too many candidates, or matches nothing (a paraphrase),
   the local embedder ranks them by meaning.
If nothing matched the keywords and the client can show questions, the user is
asked whether they want the full pages instead.

Input parameters:

- `backend` (string): Search backend, same names as deep_research. Default "auto".
- `exclude_domains`: Never results from these sites. Example: ["pinterest.com"]
- `include_domains`: Only results from these sites, subdomains included. Example: ["python.org", "stackoverflow.com"]
- `keywords`: Terms a good answer would contain, including synonyms and exact phrases. Example for "how do I make postgres faster": ["index", "EXPLAIN ANALYZE", "query planner", "vacuum"]. Strongly improves result…
- `max_passages` (integer): Passages to return. Default 8.
- `news` (boolean): Search news articles instead of the web. Results then carry their published "date". News backends: auto, bing, duckduckgo, yahoo. Pair with recency for current events.
- `num_results` (integer): Search results to consider. Default 10.
- `query` (string, required): The question or topic, in natural language.
- `recency`: Only results from the past "day", "week", "month" or "year".
- `region`: Region-language code like "us-en", "uk-en" or "de-de". Default: ddgs's own (us-en).
- `top_pages` (integer): Pages to fetch and split. Default 5.

### `read_url` (~145 tokens)

Read a page

Read one page whose URL you already have: a link the user pasted, or one from earlier
results. HTML or PDF. With a query, returns only the passages that answer it, the same
way search does; without one, the page's main text (cut to the shared budget).

Input parameters:

- `keywords`: Terms a good answer would contain, as for search.
- `max_passages` (integer): Passages to return when there's a query. Default 8.
- `query`: What you want from the page. Leave out to get the whole text.
- `url` (string, required): A public http(s) URL. Localhost and private network addresses are refused.

### `deep_research` (~440 tokens)

Deep research

Research a topic across several search terms and engines. Each term is searched on
each backend, results are re-ranked locally by relevance, duplicates are removed,
and the best pages are fetched as text.

Backends: auto, brave, duckduckgo, google, grokipedia, mojeek, startpage, wikipedia, yahoo.
\- "auto" (default): ddgs metasearch over several engines, skipping blocked ones. Most reliable.
\- "brave": fast and usually available.
\- "wikipedia": exact article lookups, best with title-like terms.
\- "google", "startpage", "yahoo", "mojeek": often blocked. Empty engines are reported
  as warnings, and if every chosen engine is empty the terms are retried with "auto".

Input parameters:

- `backends`: Backends to use. Defaults to ["auto"]. Unknown names are skipped with a warning.
- `exclude_domains`: Never results from these sites. Example: ["pinterest.com"]
- `include_domains`: Only results from these sites, subdomains included. Example: ["python.org", "stackoverflow.com"]
- `include_urls` (boolean): Whether to include each page's source URL.
- `news` (boolean): Search news articles instead of the web. Results then carry their published "date". News backends: auto, bing, duckduckgo, yahoo. Pair with recency for current events.
- `num_results_per_term` (integer): Number of results to rank per search term per backend.
- `recency`: Applied to every term. Only results from the past "day", "week", "month" or "year".
- `region`: Region-language code like "us-en", "uk-en" or "de-de". Default: ddgs's own (us-en).
- `search_terms` (array, required): 2-5 specific, related search queries covering different angles.                       Example: ["postgres query planner", "postgres index types", "EXPLAIN ANALYZE tutorial"]
- `top_k_per_term` (integer): Number of top-ranked results to keep per search term per backend.

## Diagnostics

Captured diagnostic sections: Provenance, Install scripts, Dependencies. The full working is on the page: https://verifymcp.io/servers/nkapila6-mcpsurfr/mcpsurfr#diagnostics

## Score history

- 2026-11-05: 55
- 2026-11-04: 55
- 2026-11-03: 55
- 2026-11-02: 70
- 2026-11-01: 70
- 2026-10-31: 70
- 2026-10-30: 70
- 2026-10-29: 55

## Common questions

### What is the mcpsurfr MCP server?

mcpsurfr is an MCP server listed in the public MCP registry as io.github.nkapila6/mcpsurfr. Local web search with multi-engine deep research and on-device re-ranking. No API keys. This page covers its PyPI package (mcpsurfr).

### Is the mcpsurfr MCP server safe to use?

mcpsurfr scores 55 out of 100 on VerifyMCP. We found no known CVEs affecting it as of 5 November 2026. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.

### What tools does the mcpsurfr MCP server expose?

mcpsurfr exposes 4 tools: rag_search_ddgs, search, read_url, deep_research. Their descriptions and schemas cost roughly 1,367 tokens of context every time the server is loaded.

### Is the mcpsurfr MCP server still maintained?

mcpsurfr is still listed as active in the MCP registry. We last reached this channel on 5 November 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.

### What licence is the mcpsurfr MCP server under?

mcpsurfr declares the MIT licence, which is OSI-approved. That covers the source only, and says nothing about the cost of any service it calls.

## Links

- PyPI project: https://pypi.org/project/mcpsurfr/
- Socket report: https://socket.dev/pypi/package/mcpsurfr
- Repository: https://github.com/nkapila6/mcpsurfr
- Changelog RSS feed: https://verifymcp.io/servers/nkapila6-mcpsurfr/mcpsurfr.xml
- Changelog JSON feed: https://verifymcp.io/servers/nkapila6-mcpsurfr/mcpsurfr.json
- HTML version of this page: https://verifymcp.io/servers/nkapila6-mcpsurfr/mcpsurfr