Stop writing regex.
Your AI agent can clean data for you.
Fix mangled addresses, normalize phone numbers, dedupe a messy spreadsheet, validate healthcare identifiers. Tell your agent what you want in plain English; with Snipget in its toolkit, it picks the right utility and just does it.
You ask. Your agent does it.
No setup, no glue code. Snipget's utilities show up in your agent automatically, and it reaches for them when the task fits.
You
Clean up the shipping addresses in this spreadsheet. They're a mess.
Your agent
Done. Standardized 850 addresses; 12 were missing ZIP codes, so I flagged those rows for you.
snipget · address/standardize · 850 items
Prefer to write the call yourself? The same catalog is plain REST, with Python and TypeScript clients.
One catalog, hundreds of jobs.
Hundreds of utilities and counting, from address parsing and fuzzy dedup to tiny helpers your agent reaches for a thousand times a day. Every one runs on a single value or a whole batch, so that's 300+ endpoints in all. And when your work touches biotech, chemistry, or healthcare data, this is where Snipget goes deepest.
Industry depth
Biotech
- • Gene lookup & symbol validation (HGNC)
- • Protein lookup & accession validation (UniProt)
- • Drug normalization & synonyms (Tylenol ↔ acetaminophen, RxNorm)
- • Clinical trial lookup & NCT validation (ClinicalTrials.gov)
Backed by HGNC, UniProt, RxNorm, and ClinicalTrials.gov. Stops your agent inventing gene symbols, accessions, and trial IDs.
Chemistry
- • Compound lookup (name, CAS, SMILES → formula & weight)
- • Synonym resolution (NaCl ↔ sodium chloride ↔ table salt)
- • SMILES validation & canonicalization
- • CAS Registry Number validation (format & check digit)
- • Molecular weight & composition from a formula
- • GHS hazard classification (signal word, pictograms)
Backed by PubChem (NIH), 115M+ compounds. Stops your agent inventing CAS numbers and molecular formulas.
Healthcare
- • NPI validation & taxonomy enrichment
- • DEA format & checksum
- • NUCC taxonomy lookup & search
- • Credential expansion (MD ↔ Doctor of Medicine)
- • Cert status normalization
Backed by curated reference data, refreshed on a schedule. The part you really don't want to hand-roll.
Everyday utilities
Common
- • Address parsing & standardized formatting
- • Person & org name parsing
- • Phone number normalization (international)
- • Entity match & fuzzy dedup
- • ID classification (SSN, EIN, TIN, NPI)
- • Jurisdiction (state, country, region)
Tiny helpers
- • Case conversion, whitespace, unicode fold
- • Slug, truncate, redact, checksum
- • Null detection, loose parsing
- • Format email / URL / UUID
- • Base64, hex, URL & HTML entity encode/decode
- • Extract emails, URLs & numbers from text
Developer utilities
- • Date & time math, timezones, business days
- • JSON validate, query, transform & diff
- • URL, IP / CIDR & MAC parsing
- • UUID / ULID / token / password generators
- • Unit conversion & exact number compare
- • Hashing, HMAC & JWT decode
Every tier includes everything
No feature gates. Every utility in the catalog is available on every tier including Free. Pricing scales on throughput, not which utilities you need.
It's not accuracy. It's silent failure.
Errors compound.
Frontier models still hallucinate at 10%+ on simple tasks (Vectara HHEM, Nov 2025). Across a six-step pipeline, that's ~53% accuracy! Nearly half the rows in a thousand-row spreadsheet come out wrong.
Wrong rows look right.
No exceptions raised. No confidence scores attached. They get trusted by every system downstream. You find out when a dedup misses, a report doesn't reconcile, a customer complains or never.
Your agent finds the fix.
With Snipget in the agent's MCP toolkit, it reaches for the right utility when it recognizes the task. No-code builders, low-code workflows, non-technical users, same coverage, without knowing or needing to ask.
The utility layer your AI assistant already knows how to use.
Under the hood, for the technically curious: the same API whether the caller is an agent over MCP or your script over REST.
Programmatic, not generative
Every utility is pure deterministic logic, no LLM calls. Predictable, fast, and cheap. Confidence scores tell your agent when to trust and when to escalate.
Consistent envelope
Every endpoint returns the same shape. Every error is the same format. Batch and single calls share the contract. Agents hate special cases, which is why we obsess over removing them.
OpenAPI + MCP native
Discoverable through the mechanisms agents already use. Rich OpenAPI descriptions, first-class MCP server, thin client SDKs for Python and TypeScript.
Let your agent handle it.
Free account in 30 seconds, no card required, 5,000 free calls a month. Plug Snipget into Claude or Cursor and hand off the cleanup work. That 200-line utils.py everyone's afraid to touch? Retire it.
Get started free