omnideck-mcp

OmniDeck MCP

Local, privacy-first tools for AI agents. No network calls, ever.

Some tasks are awkward to hand to an AI agent because doing them normally means pasting a secret into a website: decoding a JWT, hashing a password, scrubbing a log file before it goes to an API. This server does those locally instead.

Every tool is pure computation inside your own process. The server opens no sockets and makes no outbound requests — nothing you pass to it leaves your machine.

Install

npm install -g omnideck-mcp

Or run it without installing:

npx omnideck-mcp

Configure

Claude Desktop — add to claude_desktop_config.json:

{
  "mcpServers": {
    "omnideck": {
      "command": "npx",
      "args": ["-y", "omnideck-mcp"]
    }
  }
}

Claude Code:

claude mcp add omnideck -- npx -y omnideck-mcp

Any MCP client that speaks stdio works the same way.

Tools

redact_sensitive_data

Masks emails, API keys, credit cards, IBANs, IP addresses and phone numbers. Run it over logs, config files or user-pasted text before that content reaches an external API or a shared transcript.

Patterns are applied most-specific-first, so a key like sk-ant-… is matched whole rather than being chopped up by the generic phone-number pattern.

Contact me at [e-mail], key sk-ant-abcdefghij1234567890
→ Contact me at [EMAIL REDACTED], key [API KEY REDACTED]

Optional categories argument restricts which classes are masked.

decode_jwt

Decodes a token's header and payload and reports whether it has expired. The signature is not verified — no secret is needed, and none should be pasted anywhere. A JWT is a live credential; this exists so you never have to paste one into an online decoder.

estimate_llm_cost

Compares what a single request would cost across eight GPT, Claude and Gemini models, cheapest first. Pass text (tokens are counted exactly via gpt-tokenizer) or pass input_tokens directly. Useful before committing to a model for a large batch job.

List prices are current as of 2026-08 and are refreshed periodically — check your provider's pricing page before relying on them for billing decisions.

split_for_context

Splits a long document into chunks that fit a token budget, cutting on paragraph boundaries and falling back to sentence boundaries, so no chunk ends mid-thought.

check_output_fidelity

Flags names, numbers and dates that appear in an AI-generated summary but not in the source it was based on — the usual shape of a fabricated detail.

This is a lexical heuristic, not a fact-checker. It catches invented specifics, not faulty reasoning, and a correctly-rephrased term can be flagged. Treat the output as a list of things to verify by hand.

hash_text

MD5, SHA-1, SHA-256 or SHA-512 digest of a string, computed locally. For when the input is a password or other private value that has no business going into an online hash generator.

Privacy

• No network requests. No telemetry. No analytics. No logging of your inputs.
• Three runtime dependencies: the MCP SDK, zod, and gpt-tokenizer.
• MIT licensed — read index.js and verify all of the above; it is a single readable file.

Related

Full documentation for this server, in English and Spanish: omnideck.cc/mcp

These tools also run as free browser-based utilities, alongside ~125 others, at omnideck.cc — same principle, everything client-side.

License

MIT © AAPD Studio