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    MCP server for AI-powered QA analysis. It enables analyzing test failures, identifying root causes, suggesting fixes, classifying defects, detecting flaky tests, and generating test cases and bug reports.
    10
    ISC
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    Enables statistical A/B testing by computing Welch's two-sample t-test, Satterthwaite degrees of freedom, and two-tailed p-values, alongside time-series forecasting, anomaly detection, regression, and PCA through MCP tools.
    MIT
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    Enables agents to dynamically allocate test-time compute, including entropy-driven thinking token budgets, temperature annealing, and reflection passes, while verifying reasoning via MCTS search with process reward modeling, counterfactual backtracking, formal proof checking, and majority-vote consensus. Runs as a zero-dependency Python MCP server over STDIO JSON-RPC for integration with Claude Desktop, Cursor, or custom agent runtimes.
    MIT
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    fixRAgent, by AR Logic LLC, turns one photo of a building problem into what it is, how urgent it is (EMERGENCY, TODAY, THIS WEEK or WHENEVER), which trade to call, and what to tell the resident. For property managers, landlords and companies. NARPM member. Free Test Drive for up to 10 doors; paid plans from $39/mo. fixragent.com/pricing Remote MCP server: fixragent.com/mcp
    44
    3
    MIT
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    Enables agents to get fast, calibrated probabilistic answers from Jev (Typesafe AI) to yes/no, scale, or choice questions about provided material, without using a generative model.
    1
    8 npm
    1
    MIT
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    Enables AI agents to make pay-as-you-go AI inference requests through x402 with automatic Solana USDC payments, no API keys or registration, while enforcing configurable spending limits.
    3
    89 npm
    1
    MIT No Attribution
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    Five-layer agent memory over MCP. zenbrain_store routes each memory: steps to a procedure, emotional weight to an episode, high confidence to a pinned core memory, the rest to a semantic fact. zenbrain_recall returns results with id and layer; zenbrain_forget deletes one plus what consolidation linked to it; zenbrain_consolidate runs one sleep-like pass. Local SQLite, no account, no network call.
    5
    29
    Apache 2.0
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    Provides AI assistants with real-time web search, reasoning, and research capabilities through Perplexity's Agent API and Search API, enabling tools for search, conversational Q&A, deep research, and advanced reasoning.
    4
    47,808 npm
    MIT
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    Reads passports, ID cards and driver's licences from a photo or scan and returns the printed fields and MRZ as structured JSON. One credit ($0.01) per recognised document; nothing is charged when no document is found.
    6
    222 npm
    MIT
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    Provides local, deterministic scoring and detailed auditing of text for AI-writing patterns via two read-only tools, with no network calls or language models.
    2
    17 npm
    3
    MIT
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    Predicts the outcome of Dutch court cases dismissed, partly granted, or granted using a model trained on 609,715 rulings, with the outcome leakage measured and removed: 92% of Dutch judgment texts state the outcome verbatim, 0.1% remains after the cut, giving 78.2% accuracy against a 43.7% majority baseline. The lekkage_check tool exposes that same measurement so anyone can test a datase
    3
    1
    Apache 2.0
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    Enables reranking documents by relevance to a query through a Cohere-compatible API, so existing rerank code drops in with only a base_url change. Calls are pay-per-call in USDC via x402 or covered by a free daily tier, with no account, GPU, or model download needed.
    1
    13 PyPI
    MIT
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    Enables sending a shared context with multiple independent questions to TypeSafe's Jev model via the public OpenJEV API, returning typed judgments and probabilities (choice, score, or yes/no) instead of prose.
    5
    75 npm
    1
    MIT
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    An MCP server that seats multiple LLMs as a council, letting your assistant query them in parallel or in sequence, relay answers for cross-critique, and merge conclusions within one conversation.
    6
    35 PyPI
    2
    MIT
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    Enables Codex to consult Claude Code for a second opinion through a local stdio MCP server, exposing the ask_claude tool for text-only reviews and recommendations using existing Claude Code authentication. Codex can request findings and tradeoff analysis without allowing Claude to edit files or run commands.
    1
    1
    MIT
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    Real human judgment as agent tools -- an AI agent can ask a question and get back a structured, schema-validated JSON answer from a real quality-scored human. 16 response types (yes/no, ratings, rankings, A/B tests, sentiment, image/video/audio review, voice/video/photo capture). Fully programmatic signup with a $5 free trial credit, no card required.
    7
    64 npm
    MIT
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    Provides a structured map of 120 practical AI prompts across 6 business domains, enabling users to quickly generate complete prompts for specific tasks using slash commands or tools.
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    6 npm
    MIT
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    Connect AI agents to Jev AI (jev-ai.pro) for classification, scoring, yes/no checks, advisory action assessment, batched typed decisions and saved judges. Returns structured answers and probabilities using your Jev AI API key.
    6
    MIT
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    Furl folds repeated tool output into a hash-addressed marker, keeps the line that matters, and returns any original byte-exact the moment the agent asks for it. No summary. No guessing. Nothing thrown away.
    6
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    Apache 2.0
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    Enables AI agents to receive a structured verdict on whether a UI component need can be satisfied by existing shadcn/ui or 21st.dev components or requires a custom build, with coverage scoring against real component evidence and a Mobbin reference when needed.
    1
    191 npm
    9
    MIT
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    Enables coding agents to submit their original request, proposed plan items, and observed repository conventions for per-item necessity scoring before making edits. It returns advisory keep, simplify, or review recommendations with reasons and evidence, without blocking or modifying the plan.
    1
    12 npm
    MIT
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    Two self-hosted MCP servers: manage a local model machine (Ollama pull/switch, LoRA training) and bridge to local Ollama/vLLM for pure language processing tasks (writing, summarizing, classifying, extraction) without giving the calling agent tools or file access.
    4
    MIT
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    Industry 4.0 / IIoT AI agents for manufacturing: explain OEE losses per shift, triage machine alarms, find downtime root causes, prepare predictive-maintenance jobs and write shift reports from Unified Namespace (UNS), MQTT or historian data. Plus an industrial AI-readiness diagnostic and a vendor-neutral digital-transformation advisor. Works in Claude Code, Codex and any MCP client.
    1
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    173 npm
    MIT
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    Enables MCP clients to measure a track's loudness and peak levels, strip artifacts left by AI generators, compare mastering presets, and master single tracks or batches to streaming targets via a hosted remote server or a local stdio bridge. Tracks are supplied as public HTTPS links, with analysis, cleanup and previews free and full masters limited by a daily free quota or credits.
    9
    MIT