String Utility Belt
Related Servers
Alternatives to String Utility Belt
No user-submitted related servers found.
Related Servers
- FlicenseAqualityBmaintenanceSwiss-army-knife utility MCP server for AI agents. 18 tools for JSON validation/formatting, base64 encode/decode, hash generation, UUID generation, URL parsing, regex testing, markdown↔HTML conversion, text stats, slug generation, datetime conversion, cron parsing, text diffing, CSV↔JSON conversion, and JWT decoding. Zero API Key required185-
- AlicenseAqualityCmaintenanceProvides deterministic developer utilities as MCP tools, including UUID/password generation, hashing, encoding, JWT decoding, cron scheduling, regex execution, and text analysis. Runs entirely locally with no network calls, telemetry, or API keys.2047 npmMIT
- AlicenseNot gradedqualityCmaintenanceExposes 24 deterministic developer utilities as MCP tools — encoders and hashers, UUID/ULID and timestamp helpers, color, CSS, cron and permission converters, JSON/YAML/XML/SQL/TypeScript transformers, and a web page-to-markdown fetcher. Runs locally over stdio so agents get byte-exact results instead of approximating computations, with only the markdown fetcher making network requests.MIT
- AlicenseAqualityCmaintenanceFree, fully-offline MCP utility tools for agents: base64, UUID, JSON validation, SHA hashing, timestamps, URL codec, case conversion, and secure passwords. No API keys, no tracking, works offline - stdlib-only Python stdio server.9MIT
- AlicenseAqualityBmaintenanceEnables AI agents to perform exact, reproducible mechanical computation — text diffing, hashing, JSON querying, calendar arithmetic, deadline-bounded regex extraction, CSV parsing, similarity scoring, unit and base conversion — instead of relying on probabilistic guessing. Runs dependency-free, read-only and offline over stdio, with schema validation and hard caps on every operation so no call can hang the client.1538 npmMIT
- AlicenseNot gradedqualityCmaintenanceProvides deterministic, stateless tools for common data work including JSON, CSV, text, encoding, hashing, IDs, date/time, and number statistics.MIT
TDQS
Scored across 5 tools
Each tool occupies a distinct phase of the workflow: list_utilities discovers ids, describe_utility fetches specs, run_utility executes one, run_pipeline executes many, and detect_format only identifies. The single-vs-multi boundary between run_utility and run_pipeline is explicitly stated, and detect_format is clearly non-overlapping since it never transforms.
All five names use consistent snake_case verb_noun form (list_utilities, describe_utility, run_utility, run_pipeline, detect_format). The verbs map cleanly onto the discover/describe/run/detect lifecycle with no stylistic drift.
Five tools is well-scoped for a meta-server fronting a 247-utility catalog; exposing one tool per utility would be absurd, and wrapping the surface as discover/describe/run/pipeline/detect is economical. No redundant or filler tools.
The full lifecycle (find id, read spec, execute single, execute chained, identify unknown input) is covered with sensible encoding and error handling. Minor gaps: no dedicated validation/introspection beyond describe_utility and no explicit catalog-listing mode beyond a broad list query, but these are workable.