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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.
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    17 npm
    3
    MIT
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    CNN's Fear & Greed index for the US stock market: current score and rating, the seven component indicators, and about a year of daily history. Go standard library only, no API key required.
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    MIT
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    Extracts people (names and titles) from a company's team, leadership, or about page given a domain. Uses Apify to crawl and return structured data, with optional filters for seniority and email inclusion.
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    343 npm
    MIT
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    Enables AI assistants to answer questions about livestream advertising using GingerLive's up-to-date data on ad formats, network reach, campaign case studies, and the streamer program, as well as plan campaigns and evaluate streamer monetization.
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    MIT
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    An MCP-native research assistant — search backend, intent-routing, and writing pipeline that carries a question through search, verification, and writing, delivering whatever research you need: quick answers, verified sources, or a finished document.
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    356 npm
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    MIT
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    Enables natural language queries about the technologies behind websites and the companies running them, using the StackScan Tech Lookup API. Includes tools for domain technology lookup, company details, technology usage stats, and batch company lookups.
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    70 npm
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    MIT
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    Lets an AI agent read a YNAB budget and ask plain-language questions about it — where money went, what still needs a category, whether an account matches the bank, and when money would run out. Changes such as categorising, splitting or budgeting are read-only by default, and every write is previewed, explicitly confirmed, and undoable.
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    110 PyPI
    6
    MIT
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    Answers questions about what businesses in a given industry sell for by returning median and interquartile-range EV/EBITDA and EV/Revenue multiples by industry and deal size, with industry comparisons and year-by-year trends from disclosed 2018-2026 transactions. Every figure carries its deal count, thin cells are withheld rather than estimated, and no API key is needed.
    4
    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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    MCP server that scores the behavioral risk of a wallet on Base before sending it money. Provides a risk score, verdict, and explainable flags based on USDC payment history.
    2
    69 npm
    Apache 2.0
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    Bilingual (EN/ES) AI-writing detection that shows the evidence instead of a percentage: named tells with line and column, hidden-character inspection, and citation cross-checking against a document's own bibliography. Seven of its nine tools run entirely locally and never touch the network.
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    31
    MIT
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    Enables AI assistants to search and audit a Serato DJ library by BPM and Camelot key, browse crates, detect duplicates and missing files, and stage new crates for review before writing.
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    70 npm
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    MIT
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    Provides coding agents with file inventory, ranked search, location-aware reading, code packing, and note writing over the workspace folder through MCP, without involving a model.
    5
    428 PyPI
    69
    MIT
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    Enables small-business AI assistants to answer customer questions about hours, offerings, FAQs, staff, and booking from a single business.yaml config, with industry-specific tools and guardrails.
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    127 npm
    MIT
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    Enables reading and writing Reddit Ads campaigns, ad groups, ads, and performance reports with tiered safety controls, using the Reddit Ads API v3.
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    84 npm
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    MIT
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    Umbra is the trust layer for AI-generated code. It scores any repo 0-100 with file:line evidence (security, slop, Docker-verified build/boot, and claim receipts that catch agents lying about tests), and guards agent file writes mid-stream blocking leaked keys, alg:none JWTs, and git-hook plants before they land. Tools: scan_repo, guard_content, get_score.
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    84 npm
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    MIT
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    Checks whether a citation has been retracted, corrected, or flagged with an expression of concern by querying Crossref — including retractions that Crossref backfills from the Retraction Watch database, which publishers often never record in their own metadata. Lets an AI agent verify a DOI, or every DOI in a reference list, before using it in research or writing.
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    1
    MIT
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    Enables AI apps to work with Google Sheets in plain language: finding spreadsheets, reading and writing ranges, managing sheets, formatting, validation, protected ranges, tables, charts, and access control, with deliberate writes and destructive operations clearly marked.
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    406 npm
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    MIT
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    Enables AI agents to retrieve live product prices, stock, variants, and deal ratings from Shopify, WooCommerce, Walmart, eBay, and Amazon by pasting product links and asking about price, availability, or comparisons.
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    25 PyPI
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    MIT
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    Sigma detection rule writing, validation, and pySigma-based multi-backend conversion (Splunk, Elastic, Wazuh, Kibana) via 3 MCP tools and 3 Claude Code skills, backed by a 61-rule production corpus across 11 MITRE ATT\&CK tactic categories.
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    MIT
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    Nexus-MCP is a local MCP server for coding agents. Hybrid code search and a call graph for 10 languages give the agent the right code in one call, so it reads less. No API key, no telemetry, MIT. * 95% fewer tokens to reach the right file * About 9× faster search than Grep and Read * Live Claude Code runs on 11 repos: cost per task lower on 8 of 11
    5
    901 PyPI
    MIT
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    An MCP server that indexes a repository locally and provides keyword, semantic, hybrid, and SQL search tools, enabling coding agents to answer questions about the codebase efficiently without reading files one by one.
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    83 npm
    31
    Apache 2.0
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    Enables agents to read, search, and render PDFs confined to a single root folder, with hidden-text warnings and options to merge, split, and create PDFs from Markdown. Read-only by default, with writing tools offered only when explicitly enabled.
    4
    Apache 2.0
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    FactQL is the harness around the model: ask a question about your data and it runs the query, checks the result before you see an answer, and declines instead of guessing when it can't verify. Every answer ships with the query that ran, the rows it returned and the lineage behind it.
    2
    MIT
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    Enables a coding agent to get short, token-efficient answers about a project through grouped searches, focused symbol or section reads, and bounded read-only script output, with safety limits on paths, secrets, commands, and response size.
    3
    MIT
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    thicken turns photos of a real object into a GLB model at its real size and its metadata as JSON, read off the object by vision models and looked up in public catalogs. What it knows about each kind of object lives in a profile: a few come with thicken, and you can add your own.
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    344 npm
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    MIT
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    Enables AI agents to push and read metrics from EzStat, track counters/gauges, and ask natural-language questions about telemetry.
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    45 npm
    MIT
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    Your AI forgets everything between sessions. Rekindle fixes that. For Claude Code users who lose time re-explaining project context every session.
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    369 npm
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    MIT
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    Enables AI clients to answer questions about a signed-in host's Partelisto data, including arrivals, check-in status, SES.HOSPEDAJES submission state, and plan usage, and with granted permission to resend a guest's check-in link.
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    MIT
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    Enables an AI assistant to redact text and, more importantly, files without reading them, since file redaction and restoration happen locally and only counts are reported, keeping personal data out of the conversation. It exposes tools for redacting text, writing a redacted copy of a UTF-8 file with an owner-only restore mapping, and putting original values back offline.
    3
    MIT