Mirobody
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
Description from the maker (original English)
Check that a quoted passage appears word for word in its cited source (URL, DOI or PubMed ID).
These three are never merged into one score: opinions, measurements and popularity are different things.
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
Pick the AI app you use, then copy the settings.
You need
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"quotecheck": {
"command": "uvx",
"args": [
"quotecheck-mcp"
]
}
}
}Run this in your terminal
claude mcp add quotecheck -- uvx quotecheck-mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"quotecheck": {
"command": "uvx",
"args": [
"quotecheck-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"quotecheck": {
"type": "stdio",
"command": "uvx",
"args": [
"quotecheck-mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
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Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 8, 2026
The registry name was verified with the GitHub account feenmile, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.1.1) reached the registry 8 days ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Python (uv) on your computer.
In the same category: Mirobody, FHIR MCP Server, Google Health MCP
Servers in the same category from other makers, sorted by stars.
Reading a card:↓ Downloads per weeki★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lab results to LOINC codes and UCUM units, symptoms and diagnoses to ICPC-3. Offline, no API key.
MCP server providing seamless access to FHIR APIs for AI tools and healthcare applications
Privacy-first unofficial Google Health API v4 MCP server for health, sleep, activity, HR agents
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Does the quoted passage actually appear in the source?
AI agents (and people) often cite real sources but misstate what those sources say: real references, wrong claims. quotecheck fetches the cited source and checks that the quoted text is really there, word for word, and tells you where.
$ quotecheck "Mulberry trees" "https://en.wikipedia.org/wiki/Morus_(plant)"
{ "status": "EXACT", "char_start": 9271, "char_end": 9285, "similarity": 1.0, "snippet": "Mulberry trees", "source_final_url": "https://en.wikipedia.org/wiki/Morus_(plant)", "reason": null }
Built by Feenmile.
| status | meaning |
|---|---|
EXACT | The quote appears in the source text after normalizing whitespace, curly quotes and dash styles. Matching is case-sensitive. |
NEAR | No exact match, but a passage with similarity >= 0.90 exists (difflib SequenceMatcher ratio). snippet holds the source's actual wording. |
NOT_FOUND | Nothing in the retrievable text is close enough. similarity shows the best score found. |
SOURCE_UNAVAILABLE | The source could not be fetched or read; reason says why. |
char_start / char_end are Python string indices (end exclusive) into the plain text quotecheck extracted from the source, which you can get with quotecheck.fetch_source(source).text.
Read NEAR carefully. A NEAR result means the wording differs. A changed number ("43,548" vs "43,549") or a dropped "not" can still score above 0.90. Use the returned snippet as the quotation, or rephrase as a paraphrase.
https://... or http://... URLsdoi:10.xxxx/... (resolved through https://doi.org, following the publisher redirect)pmid:12345 (the PubMed abstract, via NCBI E-utilities efetch, plain text)The PyPI distribution is named quotecheck-mcp; the import package and the command are still quotecheck.
pip install quotecheck-mcp # library + CLI, no dependencies
pip install "quotecheck-mcp[mcp]" # also the MCP server (needs the official mcp SDK)
Python 3.10 or newer.
quotecheck "<quote>" <source>
quotecheck "the exact words" doi:10.1371/journal.pone.0000308 quotecheck --strict "the exact words" pmid:33301246 # exit 1 unless EXACT echo "a long passage" | quotecheck - https://example.org/article python -m quotecheck --help
Output is always JSON on stdout. Exit status is 0 when a verdict was printed (1 with --strict unless EXACT) and 2 for usage errors such as an empty quote.
import quotecheck
result = quotecheck.check("pmid:33301246", "A total of 43,548 participants underwent randomization") print(result.status, result.char_start, result.char_end, result.similarity) print(result.to_dict())
quotecheck.check_text(text, quote, near_threshold=0.90)
The core library uses only the Python standard library.
The server speaks MCP over stdio and exposes one tool, check_quote(quote, source).
{
"mcpServers": { "quotecheck": { "command": "quotecheck-mcp" } } }
If the script is not on your PATH, use "command": "python", "args": ["-m", "quotecheck.mcp_server"].
The tool description tells the agent to call it before presenting text as a direct quotation, and how to act on each verdict.
quotecheck fetches URLs that came from model output, so it treats them as untrusted:
http and https; URLs with embedded credentials are refused;quotecheck/0.1 (+https://feenmile.com);SOURCE_UNAVAILABLE with the reason pdf not supported in v0.1. Many DOIs resolve to a landing page whose abstract is HTML; the full text may only be in a PDF.SOURCE_UNAVAILABLE) or incomplete (NOT_FOUND).NOT_FOUND or SOURCE_UNAVAILABLE, which does not mean the quote is wrong.pmid: checks the abstract text, not the full paper.python -m unittest discover -s tests -t .
python scripts/mutation_check.py
The tests are offline. They run a local http.server fixture. Because the SSRF guard blocks loopback, tests exempt specific fixture (ip, port) pairs with quotecheck._testing.allow_loopback_endpoints, a test-only switch that is off unless a test turns it on. A second fixture server is never exempted, so the tests can prove that a redirect into loopback is refused.
scripts/mutation_check.py copies the project to a temporary directory, disables the address check, and confirms the suite fails.
MIT. See LICENSE.