Suprasūtā Markdown Notes
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# Suprasūtā Markdown Notes — MCP server
**Let Claude, VS Code and Antigravity read any document on your machine — without uploading it.**
Created by **[Narashiman Krishnamurthy](https://www.linkedin.com/in/narashimank/)**
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---
> **Licence:** free for personal, non-commercial use. See [LICENSE.md](LICENSE.md).
## What it does
AI assistants can read plain text, and some can read PDFs. None of them read
EPUB, OpenDocument, PowerPoint or a scanned image, and all of them do it by
uploading your file to a server.
This converts documents **on your own machine** and hands back Markdown that has
been tidied for a model to read — tables promoted to real Markdown tables, deep
indentation flattened, code properly fenced.
| | |
| --- | --- |
| **Documents** | PDF, Word `.docx`, Excel `.xlsx/.xls/.xlsm`, PowerPoint `.pptx`, OpenDocument `.odt/.ods`, EPUB, CSV, TSV, plain text |
| **Images** | OCR on the device, with no key and no network |
| **Audio** | Transcription — the one feature that cannot run locally |
## Tools
| Tool | What it does |
| --- | --- |
| `convert_to_markdown` | Converts one file and **saves the `.md` beside the original automatically** |
| `convert_folder_to_markdown` | Converts several files into a chosen directory |
| `save_summary` | Saves a summary the assistant wrote as `<name>.summary.md` beside the document |
| `list_supported_formats` | Lists the extensions, and which optional cloud features are configured |
### About tokens
Converting costs you nothing — it all happens locally. But **returning a long
document into the conversation does** cost tokens, at the same rate as pasting
it in by hand.
So a long conversion is saved to disk and only a short preview comes back. A
50-page PDF costs roughly 400 tokens instead of 30,000. Short documents are
returned in full, since they are cheap either way. Ask for
`return_content: "full"` to override.
## Installing
### Claude Desktop — the easy way
Download the `.mcpb` file from
[Releases](https://github.com/Narashiman-K/Markdown-Notes-MCP/releases) and
double-click it. Claude Desktop installs it and asks which folders it may read,
and optionally for API keys. No Node, no terminal, no JSON.
### Claude Desktop — from source
```bash
npm install
npm run build
node scripts/install-claude-desktop.mjs --roots "D:\your\documents"
```
Then restart Claude Desktop completely. The script patches the existing config
rather than replacing it, and writes a timestamped backup first.
`--roots` is optional but recommended: it limits which folders the server will
read. Without it, any path the assistant asks for is allowed.
To remove it again: `node scripts/install-claude-desktop.mjs --remove`
### From npm — any MCP host
```bash
npm install -g suprasuta-markdown-mcp
```
Then point your host at the `suprasuta-markdown-mcp` command, or run it without
installing:
```json
{
"servers": {
"suprasuta-markdown": {
"command": "npx",
"args": ["-y", "suprasuta-markdown-mcp"],
"env": { "MARKDOWN_MCP_ROOTS": "D:\\your\\documents" }
}
}
}
```
### VS Code and Antigravity
Both read a standard MCP configuration — the block above works as-is.
Antigravity looks in `~/.gemini/config/mcp_config.json`, or
`.agents/mcp_config.json` inside a workspace.
To run a checkout rather than the published package, replace `command` and
`args` with `node` and the absolute path to `dist/server.js`.
## Optional cloud features
Both are dormant until a key is present. Everything else works without either.
| Variable | Enables | What leaves your machine |
| --- | --- | --- |
| `GEMINI_API_KEY` | Cloud OCR, which can also describe charts and diagrams | The image, to Google |
| `ASSEMBLYAI_API_KEY` | Audio transcription | The audio file, to AssemblyAI |
Keys are read from the environment, never written to disk and never logged.
**Settings are read once, at start-up.** An MCP server is a long-running
process, so a key or folder saved while it is running does not reach it until
the host restarts. If a key you have just entered reports as not configured,
restart the host before looking for anything more complicated.
## Development
```bash
npm install # .npmrc sets include=dev — do not delete it
npm run build # stages the OCR engine, then bundles with esbuild
npm test # 19 tests against the built bundle
npm run smoke # converts every file in samples/ and reports
npm run typecheck
```
### Why the build is esbuild rather than tsc
`src/lib/convert/` is kept **byte-identical** to the copies in the Windows, web
and Android apps, so that drift can be detected rather than discovered. Those
files use extensionless imports and one Vite-specific `?url` import, neither of
which Node's own resolver accepts. esbuild resolves both, so the shared files
never need Node-shaped edits.
### The runtime hook
Three things genuinely differ between a browser and Node, and
`src/lib/convert/runtime.ts` asks the host rather than sniffing for `process`:
| Hook | Why |
| --- | --- |
| `tesseractPaths` | A browser needs URLs and its own worker; Node needs filesystem paths and must **not** be given the browser worker |
| `docxSource` | mammoth reads `arrayBuffer` in browsers and `buffer` under Node |
| `ocrImageInput` | tesseract's Node build cannot decode a `Blob`; it wants a Buffer |
Everything else is shared. `src/runtime/node.ts` supplies the Node answers and
shims exactly one browser global, `DOMParser`.
> A caution learned the hard way: that file used to define `document` too, and
> it broke OCR. tesseract.js sniffed for a DOM, found one, took the browser
> branch and died on `window is not defined`. Half a browser is worse than
> none — shim the minimum.
### Keeping the copies honest
```bash
npm run sync:check # list differences against all three apps
npm run sync:pull web # bring the web app's version in
node scripts/sync-converters.mjs --push web
```
This package is the canonical copy: it is the only one with the runtime hook
that lets identical files run in both environments, so fixes start here and
flow outward. `sync:check` reports and exits zero — drift is information, not a
build failure.
## Privacy Policy
This software collects nothing. No account, no analytics, no telemetry, and no
server of its own — document conversion happens entirely on your machine.
Two optional features send data to a third party, and only when you supply your
own API key: cloud image recognition sends the image to Google, and audio
transcription sends the audio to AssemblyAI. With no keys configured, the
software makes no network connections at all. API keys are read from the
environment, never written to disk and never logged.
Full policy, covering collection, storage, retention, third-party sharing and
contact details: **[PRIVACY.md](PRIVACY.md)**.
## Related
| | |
| --- | --- |
| Windows app | [Microsoft Store](https://apps.microsoft.com/detail/9N1S7QP2WNLX) · [source](https://github.com/Narashiman-K/Markdown-Notes-windows) |
| Web app | [markdown-notes-psi.vercel.app](https://markdown-notes-psi.vercel.app) · [source](https://github.com/Narashiman-K/Markdown-Notes-web) |
| Android | [source](https://github.com/Narashiman-K/Markdown-Notes-Android) |
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: convert one document, convert a folder, save a summary, and list supported formats. The only similar pair (single vs. folder conversion) is well differentiated by cardinality, and save_summary is explicitly limited to agent-written summaries rather than document conversion.
All tool names are lowercase snake_case and begin with imperative verbs, making the set predictable. There is a minor stylistic split between the convert_*_to_markdown pattern and plain verb_noun names like save_summary and list_supported_formats, but the overall convention is coherent.
Four tools is ideal for this narrow server: single-file conversion, batch conversion, summary persistence, and format discovery. Each tool earns its place and there is no redundancy.
The conversion workflow is fully covered: agents can convert one file or many, get content back, and handle unsupported formats. The notes side is thinner since save_summary only creates summaries with no server-side way to read, update, or delete them, but this is workable because summaries are saved as .md files on disk.