About omnideck
OmniDeck MCP provides AI agents with local privacy tools for handling tokens, logs, and text that should not be sent to websites. Its tools perform computations in-process without opening sockets or making outbound requests.
Key features
- 01Redact emails, keys, and other sensitive data
- 02Decode JWTs and check expiration
- 03Compare per-request costs across models
- 04Split long documents to a token budget
- 05Flag names, numbers, and dates in summaries
- 06Compute text hashes locally
Use cases
- 01Remove sensitive data from logs before sharing
- 02Inspect JWT headers and payloads offline
- 03Estimate model costs for batch jobs
- 04Split long documents into context-sized chunks
MCP support
The MCP server provides local privacy tools to MCP clients over stdio; its tools do not open network sockets or make outbound requests.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
Tools
6Saved tool list · updated 2w ago
| Parameter | Type | Required | Description |
|---|---|---|---|
| text | string | Yes | The text to scrub. |
| categories | array | No | Which categories to mask. Defaults to all: emails, api_keys, credit_cards, iban, ip_addresses, phone_numbers. |
Details
From the project READMEOmniDeck 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 [email protected], 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 nine 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 2026-10 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, andgpt-tokenizer. - MIT licensed — read
index.jsand 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
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.