Claude

Siddhartha Ahuja’s Blender MCP is the open-source project that puts Claude at the Blender keyboard. A Model Context Protocol server talks to a Blender add-on over a TCP socket on port 9876. From there, Claude can build shapes, paint materials, read the scene, pull free assets from Poly Haven , make meshes through Hyper3D Rodin , import Sketchfab models, and run any Python inside Blender. The repo has 19,694 stars, an MIT license, and sits at version 1.5.5. Similar add-ons exist for Unreal, Godot, Maya, and Figma. This one has the biggest crowd and the deepest tool list by far.

The Claude Agent SDK is the Claude Code engine stripped down to a library. Same agent loop, same built-in tools, same context handling, but you call it from your own Python or TypeScript code instead of the CLI. If you’ve used Claude Code to read files, run shell commands, search codebases, and edit code, the SDK points that same machinery at any problem you want. No human needs to sit in the loop.

Yes, you can point Claude Code at a 541,909-row retail dataset and walk away with a six-sheet Excel workbook, professional charts, and a parameterized report script, without opening a Python file or debugging a single line of code. The complete workflow takes roughly 15 to 20 minutes from raw data to finished output.

The goal is real delegation. Claude handles setup, cleaning, math, and charts. You focus on the right questions to ask.

Anthropic ships claude-code-action , an official GitHub Action that runs the full Claude Code runtime inside your CI/CD pipeline. It reviews pull requests, builds features from issues when someone types @claude, writes tests, updates docs, and drafts release notes. It also respects your repo’s CLAUDE.md coding rules. The runtime runs on a GitHub Actions runner, with tool use, file reads, and multi-step reasoning.

It ships with four auth backends: Anthropic API, AWS Bedrock, Google Vertex AI, and Microsoft Foundry. It also has a sister claude-code-security-review action for vuln scans, native GitLab CI/CD support, and real deployments. Deriv runs it across 700+ repos, handling 100+ PRs per week. So this has moved past the demo stage. Teams now wire it into merge gates next to linters and test suites.

Anthropic’s third-party tool rules priced agent users off Claude Opus 4.7. The cheapest working OpenClaw stack now is Z.ai’s $18/mo GLM 5 Turbo plan. Next rungs: Ollama-cloud’s $20/mo GLM 5.1, then MiniMax’s $40/mo highspeed tier. Kimi 2.6 stays API-only since local setup needs about 750 GB of RAM.

Why $1,500/mo Opus Bills Pushed Users to GLM

The pressure here is simple. Once Anthropic’s third-party tool rules kicked in, OpenClaw users on the Claude Pro CLI got nudged onto pay-per-token API access. At Opus 4.7 list pricing of $15 per million input tokens and $75 per million output tokens, agent loops add up fast. The OP of the r/openclaw PSA thread tracked his own bill at about $1,500/mo before he switched. That figure is the anchor most cost threads on the sub now cite. The pricing pain did not ease with the next model either: the community reception of Opus 4.7 leaned on token-burn complaints from power users hitting caps in minutes, which is exactly the pattern that turns an OpenClaw cron fleet into a four-figure surprise.

Hermes Agent , built by Nous Research, has taken about 30% of OpenClaw’s user base by fixing one failure: memory. The Kilo.ai synthesis of 1,300+ r/openclaw comments confirms the figure. OpenClaw still wins on multi-agent breadth and 100+ skills. The right answer depends on which failure mode hurts you more.

Why r/openclaw Is Migrating to Hermes

The most-cited migration thread on the subreddit is the 167-comment OpenClaw vs Hermes thread . The top-voted answer to “is Hermes worth a look” reads as a clean defection notice. The poster ran OpenClaw for weeks on the same workload, then switched in an afternoon: