typecast-mcp
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- AlicenseAqualityDmaintenanceEnforces structured output from LLMs by extracting JSON, validating against a shape spec, and generating retry prompts for incorrect responses.338 npm1MIT
- FlicenseNot gradedqualityNot gradedmaintenanceEnables deterministic extraction and validation of structured JSON data from inputs using a defined schema. It plugs into MCP-compatible clients like Claude Desktop, Cursor, and Windsurf to return standardized, schema-validated results.7-
- AlicenseNot gradedqualityDmaintenanceProtects AI agents from bad tool outputs, schema mismatches, and tool poisoning by validating, sanitizing, and scoring reliability of tool responses.MIT
- AlicenseAqualityBmaintenanceEnables MCP clients to extract validated typed records from unstructured text using named schemas, with schema listing and extraction tools. It returns validated JSON or tool errors, optionally using an offline parser or an OpenAI-compatible model with retries on validation failures.2MIT
- AlicenseNot gradedqualityAmaintenanceProvides deterministic JSON repair and JSON Schema validation for malformed AI agent outputs, safely fixing unambiguous errors without an LLM and refusing ambiguous cases.79 PyPIMIT
- AlicenseNot gradedqualityDmaintenanceExposes LLM output validation (schema compliance and prompt-injection detection) as an MCP tool, enabling any MCP-compatible agent to apply real-time guardrails without importing the codebase.MIT
TDQS
Scored across 2 tools
The two tools serve clearly separate purposes: one returns the JSON Schema, the other validates a concrete posting. The descriptions explicitly contrast them (the schema deliberately omits duplicate-skill and intern/experience rules that only validation enforces), so an agent cannot mistake one for the other.
Both names follow a consistent snake_case verb_noun pattern (get_..._schema, validate_...), sharing the same 'job_posting' domain noun. The naming makes the read-vs-check relationship between the tools immediately legible.
Two tools is on the thin side, but the domain (schema retrieval + validation of a single document type) is narrow enough that each tool earns its place with no filler. A slightly richer surface (e.g. a template fetch) would round it out.
The core loop is closed: fetch the schema, then validate the whole posting and get field-level errors plus the parsed result when valid, including the multi-pass rule where hidden errors surface after fixes. The only minor gap is the absence of an example/template valid posting to bootstrap authoring.