A
licenseA
qualityF
maintenanceLets MCP clients delegate private or bulk text tasks to a local OpenAI-compatible LLM while keeping data on the machine.
1
1
MIT
Razi Text Generation
Server Details
Text generation over MCP: prose, emails, blog outlines, SQL, humanizing, text diffs, fake data.
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- Status
- Unhealthy
- Uptime
- 86.8% over 61 days
- Last Tested
- Transport
- Streamable HTTP
- URL
- ChatGPT
- –
- Claude
- –
TDQS
A4.7/5.0
Scored across 7 tools
Disambiguation5/5
Each tool maps to a distinct output or transformation—comparing, email drafting, outlining, fake person data, SQL, filler prose, and humanizing—and the descriptions explicitly route overlapping cases (e.g., 'use generate_fake_data' vs 'generate_text'). No two tools can perform the same job.
Naming Consistency5/5
All seven tools follow a predictable snake_case verb_noun pattern (compare_text, draft_email, generate_*, humanize_text), with no mixed naming conventions. The generation tools share a clear generate_ prefix while keeping unique objects.
Tool Count5/5
Seven tools is well within the sweet spot and each one represents a distinct text-generation or text-processing capability. The set feels neither bloated nor thin.
Completeness4/5
The suite covers common text tasks: create prose, create specific formats (email/outline/SQL), fabricate data, rewrite, and compare. Minor gaps exist—no summarization, translation, or general-purpose edit tool—but they do not create dead ends for the stated purpose.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
7 tool updates
- First observed
compare_text - First observed
draft_email - First observed
generate_blog_outline - First observed
generate_fake_data - First observed
generate_sql - First observed
generate_text - First observed
humanize_text
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