Razi Text Generation
io.github.razikallayi/razi-text
Text generation over MCP: prose, emails, blog outlines, SQL, humanizing, text diffs, fake data.
This endpoint completed initialize and tools/list. No tool was called.
- Rank
- #4417
- Score
- 81
- Tool tokens
- 1,734
- Tools
- 7
Tools
Token cost is the o200k count of the tools list JSON, including schemas, before any tool is called.
humanize_text
Rewrite text you already have so it reads less like model output — fewer stock phrases, more contractions, varied sentence rhythm. Returns JSON { humanizedText }. Meaning is meant to be preserved but
draft_email
Write a business email body from a short brief. Returns JSON { email, cached } containing the body only — no subject line, no recipient, and nothing is sent anywhere. Choose this over generate_text wh
generate_blog_outline
Produce a markdown heading structure for a blog post — title, introduction, numbered sections with subsections, conclusion and an FAQ block. Returns JSON { outline } holding the markdown. It writes th
generate_sql
Translate a natural-language request into a SQL statement. Returns JSON { sql } containing the query text and nothing else — no validation report, no complexity score, and the query is never executed
compare_text
Compare two blocks of text line by line. Returns JSON { identical, linesCompared, changeCount, changes[] }, where each change carries a 1-based line number, a change of 'added' | 'removed' | 'modified
generate_fake_data
Produce placeholder person records for testing and fixtures. Returns JSON { type, count, records } where records is an array of strings, or of objects when type is 'user'. The values are drawn from a
generate_text
Generate filler prose — lorem ipsum, random copy or sentences — for mockups and placeholder content. Returns JSON { text, provider, cached } with the blocks separated by newlines. A language model wri
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