Tag

#ENS

234 results found

Bring your real authenticated browser session to AI coding agents. Local-first MCP server + Chrome MV3 extension. No cloud. No telemetry.
@Cubenest

peek records the user's actual logged-in browser (DOM via rrweb, console events, network metadata, optional response bodies via opt-in Deep capture) through a Chrome MV3 extension. The extension ships events through a native-messaging stdio bridge to a local MCP server (peek-mcp), which persists them to a SQLite database at ~/.peek/sessions.db. AI coding agents (Claude Code, Cursor, Cline, Windsurf) read sessions from the database via 10 MCP tools: Tool What it does list_recent_sessions List recently recorded sessions (id, origin, ts, event count). get_session_summary LLM-readable narrative summary of a session. get_session_console_errors Console errors recorded in a session. get_session_network_errors Failed/notable network requests in a session. get_user_action_before_error Last N user actions before a console error. generate_playwright_repro Generate a runnable Playwright test from a session. get_dom_snapshot Reconstruct the DOM at a given timestamp. query_dom_history Timeline of attribute/text changes for a selector. request_authorization Side-panel consent for write actions (Level 3). execute_action Dispatch a UI action (gated by permission level + destructive blocklist). Why local-first matters Every other "browser session for AI" tool ships to a vendor cloud. peek's SQLite + extension live on the user's machine — no remote endpoints, no telemetry. The privacy policy (docs/peek/PRIVACY_POLICY.md) is the source of truth. Install # 1. Add the MCP server to Claude Code claude mcp add peek -- npx -y @peekdev/mcp # 2. Install the Chrome extension from the Chrome Web Store # (link added once the CWS listing is approved)

a day ago
Swiss Whale Intelligence
@alpineflow-io

**Swiss Whale Intelligence MCP** — 45 on-chain analytics tools for **Bitcoin, Ethereum, Solana, USDT (ETH + Tron), and tokenized gold (XAUT + PAXG)**, exposed via Model Context Protocol with anonymous OAuth 2.1 (Free tier, no signup required to install). ## Tools (45 across 5 chains + meta) - **Bitcoin** (21): whale alerts, MVRV per address, Meiklejohn-canonical clusters, dormant-wakeup detection, exchange flows, mining-pool balances, SOPR, HODL waves, fear & greed, BTC indicators (Pi Cycle Top, Stock-to-Flow), entity search - **Ethereum** (5): whale alerts, ETH MVRV (3-tier doctrine), hybrid L1+L3 clusters - **Solana** (4): native + SPL whale transfers, address profiles, top movers, flow breakdown - **USDT** (4): cross-chain whale transfers (ETH + Tron), per-address activity, Tether-Treasury mint/burn events - **Tokenized Gold** (3): XAUT + PAXG whale transfers, top holders, supply mint/burn events - **Glossary** (2): plain-English definitions + search for on-chain terms (MVRV, SOPR, HODL waves, etc.) - **Benchmarks + AI + Pro** (6): BTC vs SPY/Gold/SP500 comparisons, AI-synthesized whale_explain narratives, full address history, CSV bulk export ## Quality + Trust - Anonymous OAuth 2.1 (RFC 9728 + RFC 8414), no signup to try - Methodology whitepaper published (CC-BY-4.0, SHA256-pinned): https://swisswhaleintelligence.com/whitepaper/v1.md - Listed in official MCP Registry as `io.github.alpineflow-io/swiss-whale-intelligence` v1.1.0 - Built and operated independently from Switzerland by Catering & Event Services GmbH ## Install ```bash claude mcp add btc-whale-intelligence https://mcp.swisswhaleintelligence.com/mcp ``` Or in Claude Desktop `claude_desktop_config.json`: ```json { "mcpServers": { "swiss-whale-intelligence": { "command": "npx", "args": ["-y", "mcp-remote", "https://mcp.swisswhaleintelligence.com/mcp"] } } } ``` ## Pricing Free tier (anonymous, 38 of 45 tools, 10 API calls/day, 5 AI-queries/day) → Intelligence 49 CHF/mo (full access, 10K API calls/day) → Pro 149 CHF/mo (REST API, business license) → Academic Free (verified .edu/.ac.*/.uni-*).

8 hours ago
Lexicon
@Nadine

2 months ago
Careerproof
@dontellu77

Career and workforce intelligence built on a deep HR ontology — skill taxonomies, role definitions and responsibilities, compensation and incentive structures, learning and development pathways, sourcing strategies, and role/skill evolution mapping. This structured foundation, combined with a RAG knowledge base curated from 50+ premium sources (HBR, McKinsey, BCG, Gartner, Forrester) and updated 3x daily with live web research, powers 6 guided skills and 42 MCP tools for two audiences: working professionals getting personalized career intelligence (CV optimization, salary benchmarking, career strategy), and HR/TA teams running structured talent evaluation, candidate shortlisting, compensation analysis, and consulting-grade workforce research reports. Example Use Cases (for HR/TA teams): 1. Custom Evaluation Models — Train CareerProof on your organization's existing assessment rubrics, scorecards, and evaluation criteria to build custom eval models that evaluate candidates through your specific lens. Upload your competency frameworks and historical assessments, then run inference on new candidates — scored and ranked exactly how your team would, at scale. 2. Candidate Evaluation & Shortlisting — Set up a hiring context with company profile and job description, upload candidate CVs, then batch-rank them with GEM competency scoring and JD-FIT matching. Apply your custom eval models for organization-specific scoring, or deep-dive any candidate with a 360-degree evaluation including tailored interview questions derived from skill taxonomy analysis. 3. Workforce Research Reports — Generate consulting-grade PDF reports across 16 types (salary benchmarking, skills gap analysis, org design, DEI assessment, succession planning, sourcing strategy, and more). Each report is grounded in real-time market data from premium sources and structured around HR ontology — role definitions, compensation structures, L&D pathways, and skill evolution mapping. 4. Compensation & Incentive Benchmarking — Get market-calibrated salary and total compensation intelligence for any role, location, and industry. Analysis is structured around compensation and incentive frameworks from the HR ontology, enriched with live web research and curated knowledge base data covering base salary, equity, bonuses, and benefits. Example Use Cases (for the working professional or career coach): 1. Career Intelligence Chat (Hyper-Personalized) — Ask career strategy questions and get hyper-personalized responses that fuse your CV context with deep insights from the career and workforce RAG knowledge base. Salary benchmarks calibrated to your function and location, industry disruption analysis mapped to your skill profile, and career pivot recommendations grounded in role evolution data — not surface-level answers, but intelligence drawn from the same sources that inform executive strategy. 2. CV Optimization (Hyper-Personalized) — Upload your CV and receive a hyper-personalized positioning pipeline that combines your actual experience with deep insights from our career and workforce RAG knowledge base. Market analysis calibrated to your industry and seniority, career opportunity identification grounded in role/skill evolution data, and targeted edits with trade-off analysis — not generic advice, but intelligence shaped by 50+ premium research sources and your unique career trajectory.

3 months ago
Well

5 months ago
Well
@Well

5 months ago