#MCP/Tool use

AIBAAI announces ClawKeeper v1.0, an open-source security framework for OpenClaw AI agents, combining Skill-based command policies, Plugin-based runtime monitoring, and a Watcher system-level observer. The independent Watcher is designed to block high-risk operations such as prompt injections, key leaks, rogue commands, and remote code execution, even if the agent is compromised. The paper is available on arXiv and the project code is hosted on GitHub.

AIAnthropic's Managed Agents separates the harness, sandbox, and session into independently replaceable interfaces. The source says this design let failed containers be replaced, kept tokens out of the sandbox, and reduced p50 time-to-first-token by roughly 60% and p95 by over 90%.

Why it matters: The post explains how decoupling the harness, sandbox, and session changed failure recovery, credential security, and latency, offering a reusable architecture pattern for long-running agents.

AIMckay Wrigley predicts AI tools will within 6-12 months autonomously use any software, clone it in a weekend, monitor it for updates, and add custom features. He frames this as a future where users never need to operate their computer themselves. The prediction follows a referenced Claude Code update adding computer use in research preview for Pro and Max plans.

AIAndrej Karpathy argues that the hardest part of building a deployed app is not the code but the DevOps work of assembling services, API keys, payments, auth, and deployment. He says the goal is for agents to handle this entire lifecycle as code, with agent-native CLI and API access instead of manual web clicking. He calls it a from-scratch redesign that is only now barely technically possible.

AICognition reports merging 659 Devin PRs into its own codebase last week, up from 154 in its best week in 2025. The post describes internal workflows across web, Slack, Linear, CLI, and API, including Devin Review for PR diffs and bug catching, a daily design system audit, automated bug triage on Linear, and DANA for data analysis.

Why it matters: The post shows concrete workflows for using Devin across Slack, Linear, and code review, with specific usage figures that help teams judge fit for their own engineering processes.

AIThe Codex app, a desktop app for agentic coding, launched with features including worktrees for parallel agent sessions, Skills, MCP connections, compaction, and automations. The author, who says they stopped opening their AI IDE for four days, now manages multiple Codex agents as a reviewer rather than writing code directly.

AIMoonshot AI released Kimi K2 Thinking, an open-source thinking model that interleaves step-by-step reasoning with tool calls across 200 to 300 sequential invocations. The model is a 1T-parameter mixture-of-experts with 32B activated parameters and a 256k context window, and it uses native INT4 quantization for roughly 2x faster generation. The model card reports benchmark results on HLE, BrowseComp, and other tests, and recommends vLLM, SGLang, or KTransformers for deployment.

Why it matters: The model card gives benchmark tables, quantization details, and deployment settings, letting readers compare Kimi K2 Thinking against GPT-5 and other models on specific tasks.

AICognition's Devin is now compatible with the Model Context Protocol (MCP), letting users connect favorite MCP servers through a new MCP Marketplace found in Settings. The source cites example uses including querying Datadog and Sentry logs, creating Notion docs, Google Docs, and Linear tickets, and interacting with Figma, Airtable, Stripe, and Hubspot.

AICognition launched the official DeepWiki Model Context Protocol server, which is free and requires no login or authentication. It gives programmatic access to ask_question, read_wiki_contents, and read_wiki_structure for GitHub repositories indexed on DeepWiki.com. Private repositories require a Devin account with GitHub connected, and open-source maintainers can apply for $500 in Devin credits.

Why it matters: The source names the three tools and the access path, showing how indexed GitHub repositories can be queried programmatically without login.

AILinktree has used Devin, Cognition's AI software engineer, to merge roughly 100 pull requests in a month, mostly fixing customer-reported bugs and implementing small features. The engineering team also used Devin to add support for new social media platforms, launching five Devins, one per repo and PR, and later used the Devin API with a Playbook script to spawn multiple Devins for multi-repo features. The team says Devin works best on tasks an engineer could finish in a couple of hours.

AICognition's December 2024 Devin update lets users tag Devin in Slack threads and ask it to create PRs, with Devin automatically responding to PR comments and lint failures. The update adds Repo Knowledge that Devin generates by scanning repositories, an Agency setting that makes Devin propose plans before executing complex tasks, and a REST API for structured input and output. Devin also gained faster session startup and enterprise options such as Okta single sign-on.