Context7
by upstash
Feeds AI the latest docs for libraries and frameworks before it answers, so code it writes does not use outdated, removed functions.
Computer or cloud★ 64,224MITUpdated yesterday
Install
Robot Skill Hub
Overview
Description from the maker (original English)
Search robot code and exact-version findings; check evidence before preparing with the Hub CLI.
PopNx MCP’s three pillars
These three are never merged into one score: opinions, measurements and popularity are different things.
- User voiceiNo reviews yetReviews open together with accounts in a later step
- Our basic checksi3 of 3 passedChecked from public information; code not scanned yet
- UsageiNot measured yet★ –
What you can do with it
We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
- Connection: Runs in the cloud
- Transport: Streamable HTTP
- Category: Search & AI memory
Install
Pick the AI app you use, then copy the settings.
Before you install
- Basic checks: 3 of 3 passed
- Runs on the maker’s server: what you ask it goes through their server.
- Can do 4 things (tools) start_robot_task, find_robot_skills, inspect_robot_skill, get_hub_capabilities
- The registry lists no key to fill in.
You need
- Runs in the cloudNothing to install; it connects over the internet
Which app do you use?
Pick your app above. We remember it, so next time the button says “Install in …”.
Works in Claude on the web, desktop and mobile:
- Open Settings → Connectors
- Press Add custom connector
- Paste the address below and press Add
- If it asks you to sign in, sign in with the maker
https://api.superfastrobotics.com/mcpRun this in your terminal
claude mcp add --transport http robot-skill-hub https://api.superfastrobotics.com/mcpOr copy the settings yourself
Paste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"robot-skill-hub": {
"url": "https://api.superfastrobotics.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Or copy the settings yourself
Paste into .vscode/mcp.json in your project
{
"servers": {
"robot-skill-hub": {
"type": "http",
"url": "https://api.superfastrobotics.com/mcp"
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
ChatGPT connects only to servers on the internet:
- Open ChatGPT on the web → Settings → Connectors (Apps)
- Press Create or Add (some plans need Developer mode under Advanced first)
- Paste the address below, give it a name and save
- If it asks you to sign in, sign in with the maker
https://api.superfastrobotics.com/mcpMenu names can differ slightly by plan and over time.
Your choice stays on this device in a cookie; no account needed.
These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
What it can do
Tool names and descriptions exactly as the server reported them on Nov 7, 2026. The maker wrote them, not us; we show them as plain text.
start_robot_taskFind an executable starting point for a robot task. Default compact response: one candidate, source pins, environment, evidence/recall summaries and setup argv. Use detail=execute for the complete execution contract in this same lightweight response; otherwise read selected.contr
find_robot_skillsUse for broad robotics source/reference discovery or a small candidate-only list. For an executable starting point with prior fixes and setup argv, prefer start_robot_task. Use short task keywords, or query_mode=task with known runtime/robot filters for English sentences. Follow
inspect_robot_skillUse after selecting a search result. detail=contract returns the complete execution contract without code or recall; otherwise inspect the full record and prior fixes. Read a pinned recipe/reference with up to three exact-version entries per findings/community channel as untruste
get_hub_capabilitiesRead public discovery, preparation, contribution and task-memory capabilities, local CLI onboarding links and current catalog counts. No authentication is needed for reads.
Basic checksi
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
- ✓ Pass
Maker matches the repo
The registry name was verified with the GitHub account Superfast-Robotics, which owns the repo
- … Not checked yet
Still maintained
We have not read this repo from GitHub yet
- … Not checked yet
Has a licence
We have not read this repo from GitHub yet
- ✓ Pass
Endpoint responds
Responded in 97 ms (HTTP 200)
- – Not applicable
Sign-in with OAuth
No sign-in needed
- ✓ Pass
No hidden instructions in tool descriptions
Read 4 tool descriptions and found no hidden instructions to the AI
Compared with others in Search & AI memoryi
- More stars than 0% of the other 7284 servers in this category
- Published to the registry more recently than 70% of the other 7284 servers in this category
- Basic checks equal to or better than 100% of the other 7284 servers in this category
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
Common questions
Is Robot Skill Hub safe?
It passed 3 of 3 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
What keys or codes does it need?
The registry does not list a required key, though some servers ask you to sign in on first use.
Does it run on my computer or in the cloud?
It runs in the maker’s cloud. Connect over the internet with nothing to install, but what you send passes through the maker’s servers.
Is it still maintained?
The GitHub repo last changed –, and the latest version (0.5.4) reached the registry 16 days ago.
Which apps can use it?
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. It connects by URL, so apps that accept remote MCP servers work too, such as ChatGPT in developer mode.
What can I use instead?
In the same category: Context7, Codebase Memory, Exa
Alternatives
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Codebase Memory
by DeusData
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Runs on your computer★ 48,148MITUpdated 21 days ago
Install
Exa
by exa-labs
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Runs in the cloud★ 5,213MITUpdated last month
Install
README from the maker
Open the README
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Robot Skill Hub — Robotics Skills Catalog for AI Agents
Discover robotic skills for AI agents. A public repository of reusable robot code, executable recipes and shared fixes. Find and reuse robot skills for motion planning, manipulation, kinematics and simulation. Inspect pinned code, compatibility and execution evidence through public HTTPS, MCP or the CLI; prepare a matching environment and share useful corrections. Browse concrete skill examples.
Reuse the fix. Keep the context lean. Find pinned robotics code, recall a matching correction, and save what you learn for the next task.
CLI inspection JSON: 17% fewer tokens. Same fields. Two-link IK regression: 12/24 → 24/24 targets passed after saved-fix reuse. Measurements and reproduction.
- Agent contract
- Search JSON | OpenAPI
- Read-only MCP:
https://api.superfastrobotics.com/mcp - Catalog and source references | Published findings
Public reads need no account, GPU or simulator. Discovery never executes robot code.
Task-specific entrypoints: robot-motion-planning, robot-kinematics, robot-trajectory. Ten reproducible robotics problems provide pinned input, correction and evidence in HTML, Markdown and JSON. ROS-MCP and RAI/LangChain examples connect lookup to existing development workflows.
Small HTTP installation, without a Git clone: npx skills add https://hub.superfastrobotics.com --skill robot-motion-planning. Skill index and checksums.
Robot, environment and task coverage | Coverage API. Current-version completions, failed attempts and unexecuted recipes are counted separately; reference labels describe source coverage rather than verified robot support.
Current execution and reference coverage
194 preparation recipes: 169 completed operations/tasks, 14 failed current task attempt and 11 without a current task run. Unbound evidence: 0.
| Runtime | Declared robot / model | Domain | Prepared | Passed | Failed | No task run |
|---|---|---|---|---|---|---|
| dm-control | ball_in_cup | simulation | 1 | 0 | 1 | 0 |
| dm-control | cartpole | simulation | 2 | 2 | 0 | 0 |
| dm-control | finger | simulation | 1 | 0 | 1 | 0 |
| dm-control | pendulum | simulation | 1 | 1 | 0 | 0 |
| dm-control | point_mass | simulation | 2 | 2 | 0 | 0 |
| dm-control | reacher | simulation | 2 | 2 | 0 | 0 |
| genesis | panda | simulation | 2 | 2 | 0 | 0 |
| gymnasium-robotics | fetch | simulation | 3 | 3 | 0 | 0 |
| gymnasium-robotics | point-mass | simulation | 3 | 3 | 0 | 0 |
| lerobot | pusht-2d-pusher | simulation | 1 | 0 | 1 | 0 |
| maniskill | panda | simulation | 8 | 5 | 1 | 2 |
| maniskill | panda_stick | simulation | 2 | 0 | 0 | 2 |
| maniskill | panda_wristcam | simulation | 2 | 0 | 0 | 2 |
| maniskill | so100 | simulation | 1 | 0 | 0 | 1 |
| maniskill | xarm6_robotiq | simulation | 4 | 0 | 0 | 4 |
| metaworld | sawyer | simulation | 50 | 49 | 1 | 0 |
| mink | iiwa | simulation | 1 | 1 | 0 | 0 |
| mink | panda | simulation | 1 | 1 | 0 | 0 |
| mink | ur5e | simulation | 1 | 1 | 0 | 0 |
| mujoco | agilex_piper | simulation | 1 | 1 | 0 | 0 |
| mujoco | aloha | simulation | 1 | 1 | 0 | 0 |
| mujoco | arx_l5 | simulation | 1 | 1 | 0 | 0 |
| mujoco | dynamixel_2r | simulation | 1 | 1 | 0 | 0 |
| mujoco | flexiv_rizon4 | simulation | 1 | 1 | 0 | 0 |
| mujoco | flexiv_rizon4s | simulation | 1 | 1 | 0 | 0 |
| mujoco | franka_emika_panda | simulation | 1 | 1 | 0 | 0 |
| mujoco | franka_fr3 | simulation | 1 | 1 | 0 | 0 |
| mujoco | franka_fr3_v2 | simulation | 1 | 1 | 0 | 0 |
| mujoco | google_robot | simulation | 1 | 1 | 0 | 0 |
| mujoco | hello_robot_stretch | simulation | 1 | 1 | 0 | 0 |
| mujoco | hello_robot_stretch_3 | simulation | 1 | 1 | 0 | 0 |
| mujoco | i2rt_yam | simulation | 1 | 1 | 0 | 0 |
| mujoco | kinova_gen3 | simulation | 1 | 1 | 0 | 0 |
| mujoco | kuka_iiwa_14 | simulation | 1 | 1 | 0 | 0 |
| mujoco | low_cost_robot_arm | simulation | 1 | 1 | 0 | 0 |
| mujoco | rethink_robotics_sawyer | simulation | 1 | 1 | 0 | 0 |
| mujoco | robotis_omy_3m | simulation | 1 | 1 | 0 | 0 |
| mujoco | robotstudio_so101 | simulation | 1 | 1 | 0 | 0 |
| mujoco | seeed_rebot_devarm | simulation | 1 | 1 | 0 | 0 |
| mujoco | shadow_dexee | simulation | 1 | 1 | 0 | 0 |
| mujoco | stanford_tidybot | simulation | 1 | 1 | 0 | 0 |
| mujoco | trossen_vx300s | simulation | 1 | 1 | 0 | 0 |
| mujoco | trossen_wx250s | simulation | 1 | 1 | 0 | 0 |
| mujoco | trossen_wxai | simulation | 1 | 1 | 0 | 0 |
| mujoco | trs_so_arm100 | simulation | 1 | 1 | 0 | 0 |
| mujoco | ufactory_lite6 | simulation | 1 | 1 | 0 | 0 |
| mujoco | ufactory_xarm7 | simulation | 1 | 1 | 0 | 0 |
| mujoco | unitree_go2 | simulation | 1 | 1 | 0 | 0 |
| mujoco | unitree_z1 | simulation | 1 | 1 | 0 | 0 |
| mujoco | universal_robots_ur10e | simulation | 1 | 1 | 0 | 0 |
| mujoco | universal_robots_ur5e | simulation | 1 | 1 | 0 | 0 |
| panda-gym | franka-panda | simulation | 5 | 2 | 3 | 0 |
| pybullet | synthetic-seven-axis-or-procedural-scene | simulation | 12 | 12 | 0 | 0 |
| pythonrobotics | mathematical-model | computation | 28 | 28 | 0 | 0 |
| robosuite | IIWA | simulation | 4 | 3 | 1 | 0 |
| robosuite | Jaco | simulation | 4 | 1 | 3 | 0 |
| robosuite | Kinova3 | simulation | 4 | 3 | 1 | 0 |
| robosuite | Panda | simulation | 4 | 4 | 0 | 0 |
| robosuite | Sawyer | simulation | 4 | 3 | 1 | 0 |
| robosuite | UR5e | simulation | 4 | 4 | 0 | 0 |
Completion evidence covers 33 computations and 136 simulations across 60 exact environment combinations. Physical robot completions: 0. Recipe counts are not unique robot counts or general success rates. Older versions do not verify changed code.
| Task level | Prepared | Passed | Failed | No task run |
|---|---|---|---|---|
| Algorithm / sensing | 39 | 39 | 0 | 0 |
| Motion / control | 49 | 49 | 0 | 0 |
| Task | 106 | 81 | 14 | 11 |
1897 source references across 67 frameworks. References are upstream declarations, not Hub execution evidence.
| Reference framework | Records |
|---|---|
| mujoco-menagerie | 221 |
| webots | 193 |
| genesis | 118 |
| pinocchio | 76 |
| drake | 73 |
| franka-description | 72 |
| ros2-control | 72 |
| ur-description | 65 |
| Other 59 frameworks | 1007 |
| Declared reference robot category | Records |
|---|---|
| source-defined | 1091 |
| arm | 301 |
| humanoid | 104 |
| manipulator | 83 |
| mobile-manipulator | 65 |
| legged | 59 |
| aerial | 41 |
| wheeled | 36 |
| dexterous-hand | 35 |
| quadruped | 18 |
| mobile | 9 |
| marine | 1 |
Robot categories and task/capability tags can overlap. Generic labels are preserved; supported physical robots are not inferred.
All robot, environment and task tables | Compact coverage API | Complete coverage JSON
Executable skills and interfaces: 98 preparation recipes, including 45 numerical/synthetic adaptations and 36 diverse robot simulation adapters. Inputs and outputs declare units, frames, abstraction level and runtime evidence. Indexed references link to matching prepared adaptations without changing the reference's evidence.
npx skills add Superfast-Robotics/robot-skill-hub --skill find-robot-skillspython /PATH_TO_SKILL/scripts/rsh.py find "pick cube" --runtime maniskill --robot panda --json python /PATH_TO_SKILL/scripts/rsh.py inspect SKILL_ID --project . --json python /PATH_TO_SKILL/scripts/rsh.py prepare SKILL_ID --project ./experiment --plan --json
For an MCP client supporting Streamable HTTP, use its remote-server configuration:
{"mcpServers":{"robot-skill-hub":{"url":"https://api.superfastrobotics.com/mcp"}}}Clients supporting Agent Plugins 1.0.0 can use the small read-only connection package. Its manifest and MCP configuration include no CLI bundle or catalog snapshots; see the package README for client verification scope.
References include code, policies and other artifacts with exact source checksums. Use a reference's inspected fetch_source_args with rsh.py and append --project DIR --json to retrieve one verified file as inert data. This does not require a runtime adapter or install the source as an agent skill. Supported recipes use prepare; runtime evidence is limited to the exact configuration and seed recorded with each recipe. Existing project locks never silently change.
Recall previous setup work with rsh.py inspect SKILL_ID --project DIR --json. Preserve a useful finding with save SKILL_ID --project DIR --finding FILE --json. Local experience is immediately reusable. For already-authorized public project scope, join enrolls an installation and enables automatic publication, without a maintainer token or PR approval. Immutable variants and actual reuse outcomes remain tied to exact source pins. See the community loop.
Community data is contributor-reported and archived hourly on the community-data branch. It never silently replaces canonical code or establishes runtime verification. New canonical sources (register) and changes to curated recipes retain their separate reviewed PR channel.
Quickstart | New skills | Task memory | Patch contributions | Privacy
Verification evidence | Development and deployment
Hub platform code is Apache-2.0 licensed. Hub-authored robotics execution adapters and their templates are MIT licensed. Referenced artifacts retain their original licenses and notices; see license scope. The company website is separate from the Hub.