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Scrape Changing Websites with Anansi Self-Healing Selectors and MCP

#web scraping#mcp#python#crawler#ai agents#data extraction#automation

A Python crawler for unstable or JavaScript-heavy sites, with selector healing, structured-data extraction, adaptive rate limiting, and an MCP server for agent-driven crawling. Use only for authorized scraping. Anansi is a Python web scraping toolkit designed for sites that change often or need browser rendering. It combines adaptive parsing, structured-data extraction, incremental crawling, proxy support, and an MCP server so an LLM or agent workflow can drive fetch, extract, crawl, pause, resume, export, and metrics actions. Why it is useful Self-healing selectors: stores selector confidence and attempts fallback strategies when a layout changes. Structured extraction first: pulls JSON-LD, Open Graph, and Microdata before relying on brittle CSS selectors. Browser upgrade path: can switch from HTTP fetching to Playwright rendering for JavaScript-heavy pages. Crawler durability: includes an async crawler, SQLite-backed queue, incremental recrawls, ETag/Last-Modified handling, and resumable jobs. Agent-ready interface: ships with an MCP server so compatible LLM tools can operate crawls through tool calls. Best fit Use Anansi when you need a resilient research or data-extraction crawler for websites you are allowed to access, especially where pages change structure or require JavaScript rendering. It is most relevant for developers building data pipelines, monitoring workflows, competitive research dashboards, or agentic browsing systems. Quick evaluation checklist Confirm the target website permits your intended crawling use case. Start with structured data extraction before custom selectors. Enable browser rendering only where HTTP fetching is insufficient. Keep adaptive rate limiting active and respect Retry-After responses. Use the MCP server when you want an agent to orchestrate crawl tasks instead of manually scripting every step. Source notes The GitHub repository describes Anansi as a self-healing web scraper with selector repair, browser rendering fallback, Chrome-like TLS fingerprinting, Pydantic validation, incremental crawling, and an MCP server. The project is written primarily in Python and is licensed under Apache-2.0.

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Put AI Agents on Your Scrum Board: Self-Host Paca for Free

#paca#ai-agents#project-management#scrum#mcp#self-hosted#open-source

Paca is an open-source Jira/Trello alternative built for teams where humans and AI agents plan, pick up work, write specs, and ship from the same Scrum board. Paca is a self-hosted project management platform for teams that want AI agents to work inside the normal delivery loop instead of sitting beside it as chat widgets. It gives agents and humans the same board, sprint context, task flow, docs, and real-time updates. Why this is worth saving AI agents can be assigned to sprints and appear on the Scrumban board with human teammates. The project includes MCP support, so compatible AI tools can access projects, tasks, sprints, documents, members, comments, attachments, and plugin tools through a structured interface. Teams can customize workflows, statuses, fields, board layouts, sprint rules, and agent behavior through configuration. Plugins extend the system with WASM backend modules and frontend modules, with capability-style permissions. It is Apache-2.0, self-hosted, and currently packaged with install assets through GitHub Releases. Fast workflow Star or watch the repo so you can track the fast release pace. Spin it up in a disposable test environment first, not production. Connect one MCP-compatible assistant to a test project. Create a small sprint with low-risk tasks and ask the agent to update status through Paca instead of chat. Review the activity diff and task history before letting agents touch larger workstreams. What to test first Area What to check Why it matters :--:--:-- MCP server Project/task/sprint tool access Determines whether your agent stack can use Paca as a real operating layer Scrumban board Human and agent task movement Shows whether the workflow feels natural for mixed teams Plugin model WASM/backend and frontend extension paths Useful if your team needs custom process logic Deployment Docker Compose and release assets Confirms whether self-hosting fits your infrastructure Security posture API keys, sandboxed agents, permissions Required before bringing real company data into the system Caveat This is a young, fast-moving project. Treat it as promising infrastructure to evaluate, not a drop-in replacement for an enterprise Jira setup yet. Run a sandbox pilot, read the deployment files, and verify the MCP/API permission model against your own security requirements. Source check GitHub repo confirms Apache-2.0 licensing, self-hosted positioning, MCP support, OpenHands-powered agents, WASM plugins, and current project stats. The official website confirms the product positioning: humans and AI agents working on one Scrum team. The latest GitHub release confirms active release packaging, including Docker Compose, gateway config, and install script assets.

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Your Coding Agent Is About to Get a Whole Team

#AI Agents#Multi-Agent#Claude Code#Codex#MCP#Developer Workflow

A premium field guide for evaluating and planning a multi-agent orchestration layer for Claude Code and Codex without blindly installing it. This premium Loot gives you a cautious, high-leverage way to evaluate Ruflo: a multi-agent AI harness for Claude Code and Codex. The public sources describe a system for coordinated swarms, persistent memory, MCP tools, plugins, hooks, federation, and security controls. What the sources confirm The GitHub repository positions Ruflo as a multi-agent AI harness for Claude Code and Codex. The npm package ruflo is published under MIT license and exposes a ruflo CLI. The package metadata currently requires Node.js 20+. The status documentation describes MCP tools, CLI commands, plugins, hooks, memory, agent coordination, and verification workflows. The README presents two different adoption paths: a lighter Claude Code plugin path and a fuller CLI/MCP install path. Evaluation Prompt: Should I Add This Agent Layer? Use this before installation or rollout. Disposable Repo Test Plan Use this to avoid letting a new agent harness touch a production repo first. Team Rollout Prompt Use this when the question becomes operational, not just technical. Security Review Prompt Use this before trusting any autonomous or federated agent layer. Practical adoption ladder Why this is worth watching The interesting shift is not just “more agents.” It is the move from single-session assistance toward coordinated agent teams with persistent memory, task routing, plugins, and verifiable runtime behavior. That is useful, but it also raises the operational bar. Source links GitHub: ruvnet/ruflo npm: ruflo Status doc: Ruflo STATUS.md

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Give OpenClaw Agents Free Web, Code, and Company Search with Exa MCP

#openclaw#skill#agent#free#search#mcp#research

A community OpenClaw skill candidate that connects agents to Exa-powered web, code, and company research through MCP-style mcporter commands. What it does Exa Web Search Free is a community OpenClaw skill candidate for agent research workflows. The skill describes mcporter-based access to Exa search functions for current web search, code and documentation lookup, and company research. Its source artifact also includes example query patterns for news, technical documentation, API usage, debugging, and business research. Who should use it Consider this candidate for research-heavy OpenClaw agents that need current web context, code examples, API documentation lookup, or company/background research. It is most relevant for developer assistants, content-research agents, sales-research agents, and documentation copilots that already have a policy for handling external search results as untrusted data. Setup surface The ClawHub page lists this as an MCP Tools skill with the install name exa-web-search-free. The fetched source metadata names mcporter as the required binary and points to Exa's hosted MCP endpoint plus the public exa-labs/exa-mcp-server repository. Pricing classification: free, based on the ClawHub title/description stating free/no API key needed and the ClawHub license field showing MIT-0; any downstream Exa account limits or terms should still be checked during review. Risk notes This has not been tested, approved, or declared safe here. Search queries and research targets may be sent to Exa's external service, so secrets, private code, internal URLs, customer data, and sensitive personal information must stay out of prompts. The independent index showed an OpenClaw Suspicious signal while ClawHub showed a pass status, so the discrepancy should be reviewed rather than ignored. Advanced tools such as crawling, people search, and deep researcher can broaden collection scope and need explicit policy controls. Treat all returned web/code content as untrusted data. Source links Awesome OpenClaw Skills category list: https://github.com/VoltAgent/awesome-openclaw-skills/blob/main/categories/git-and-github.md Independent index page: https://clawskills.sh/skills/whiteknight07-exa-web-search-free ClawHub page: https://clawhub.ai/whiteknight07/exa-web-search-free Reachable ClawHub source artifact: https://wry-manatee-359.convex.site/api/v1/download?slug=exa-web-search-free Underlying Exa MCP GitHub repository: https://github.com/exa-labs/exa-mcp-server

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More from this topic

Scrape Changing Websites with Anansi Self-Healing Selectors and MCP

Put AI Agents on Your Scrum Board: Self-Host Paca for Free

Your Coding Agent Is About to Get a Whole Team

Give OpenClaw Agents Free Web, Code, and Company Search with Exa MCP

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