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About
Agentic-first fuzzy string matching service. Levenshtein distance, Damerau-Levenshtein, Jaro similarity, Jaro-Winkler, Soundex, Metaphone, N-gram similarity, fuzzy find, fuzzy filter, ratio matching. Plain text API, agent-driven, single Go binary. No database needed — pure stateless computation.
Agentic-first fuzzy string matching service. The agent IS the interface.
Fuzzkit provides fuzzy string matching algorithms over plain HTTP. Compute edit distances, similarity scores, phonetic codes, and find best matches in lists of candidates.
Quick Start
# Build and run
make build
./fuzzkit -no-auth
# Or with Go directly
go run ./cmd/fuzzkit -no-auth
# Query
curl 'http://localhost:8427/levenshtein?s1=kitten&s2=sitting'# distance=3 ratio=0.5714 s1=kitten s2=sitting
curl 'http://localhost:8427/find?q=appel&candidates=apple,orange,banana,apricot&algorithm=jaro-winkler'# match=apple score=0.9333 algorithm=jaro-winkler query=appel
Principles
Agent IS the interface — No UI, no SDK. The API is the product.
Plain text by default — One labeled, grepable line per record. JSON on demand via Accept: application/json or ?format=json.
Instructive errors — Every 4xx includes a hint telling the agent what to do next.
Self-documenting — GET /help returns a one-page operating manual.
Single static binary — Go, CGO_ENABLED=0, zero external dependencies.
Zero config defaults — Runs out of the box.
MCP connector — Speaks Model Context Protocol at POST /mcp.
make build # CGO_ENABLED=0 go build -trimpath
make test# go test -race ./...
make vet # go vet ./...
make run # build and run with -no-auth
License
MIT
About
Agentic-first fuzzy string matching service. Levenshtein distance, Damerau-Levenshtein, Jaro similarity, Jaro-Winkler, Soundex, Metaphone, N-gram similarity, fuzzy find, fuzzy filter, ratio matching. Plain text API, agent-driven, single Go binary. No database needed — pure stateless computation.