"Technology pre-research resources" matching MCP servers:

Enables capturing web evidence, freezing content-addressed snapshots, and comparing research agents on the same sources with traceable access and quotations.

Enables deliverable conformance and evidence-chain checks by turning requirements into executable specs, validating numbers against a provenance ledger, and auditing PDF/OOXML metadata and archive manifests.

The checklist you wish someone had given you before launch.

Fact-checks and fixes AI outputs by catching hallucinations, repairing broken JSON, and correcting errors before they reach users, with tools for verification, validation, and correction.

Enables AI-powered document analysis and querying for project documentation using vector embeddings stored in Redis. Supports document upload, context-aware Q\&A, automatic test case generation, and requirements traceability through OpenAI integration.

A remote MCP server exposing 3 tools via Model Context Protocol: score_prompt (free, grades any LLM prompt A-F on 0-40 scale), optimize_prompt (returns optimized prompt + dimension breakdown, $0.025 USDC), and compare_models (Claude vs GPT-4o head-to-head, $1.25 USDC). Remote HTTP server at /api/mcp.

Screen-reader navigation cost analyzer. Measures how hard it is for assistive-technology users to discover, reach, and operate interactive targets on the web.

Exposes MAID Runner validation tools (validate, snapshot, test) as MCP tools, resources, and prompts for AI agents like Claude Code and Aider, enabling seamless integration with AI development workflows.

An MCP server that grades prompts against a validated rubric, tracks real outcomes, and provides guidance grounded in research on what predicts good results.

Enables LLM agents to programmatically inspect, debug, and test other MCP servers by wrapping the MCP Inspector CLI. Supports listing and calling tools, reading resources, and testing prompts on both local and remote MCP servers.

Exposes a set of honesty SDK TypeScript libraries as MCP tools so a coding agent can check grounded citations, corroborate evidence, test payout and mutation invariance, score trust and anonymous authenticity, validate provenance claims, track a claims registry and tamper-evident audit chain, and grade recommendations against outcomes. It also scaffolds two runtime kits for agent authorization receipts and pre-call cost governance.

A high-performance, multi-protocol API mock server with 18 built-in MCP tools for managing HTTP, GraphQL, gRPC, WebSocket, MQTT, SSE, and SOAP mocks, chaos engineering, stateful CRUD resources, and request verification.

Enables pre-launch website checks for link previews, SPA routes, and security headers before sharing URLs.

Connects AI coding assistants to TestCollab for managing test cases, plans, and suites directly through natural language. It enables users to create, update, and query testing resources within integrated development environments and AI chat clients.

An MCP server that provides tools for certificate verification, equivalence proving, and pre-registration sealing, enabling AI agents to re-derive verdicts from artifacts rather than trust assertions.

Provides structured, sandboxed test and lint feedback for coding agents, returning compact typed verdicts with failure fingerprints instead of raw runner output. It enables impact-selected test execution in isolated containers, distinguishing pre-existing failures from regressions.

A research harness for measuring whether MCP clients preserve informed consent when tool definitions change after approval.

Enables local auditing of trading strategies through MCP checkers for point-in-time data provenance, pre-trade order validation, and regime-fragility testing, while deferring promotion verdicts to a hosted service.

Enables AI coding agents to run fast, sandboxed pre-flight validation—tests, type-checking, linting, security audits, Git safety scans, and fix suggestions—before committing or pushing code, with instant caching and optional Docker isolation.

Enables building and evaluating shopping/support agents against a deterministic synthetic retail store with in-memory fixtures. Provides tools, resources, and prompts for product search, cart and order flows, inventory, and policy retrieval over stdio or Streamable HTTP.