About AGILEX Docs
AGILEX Docs is a read-only MCP server for searching and reading official AgileX Robotics manuals, protocol references, firmware notes, SDK articles, and FAQs. It helps developers consult product documentation while integrating AgileX hardware.
Key features
- 01Full-text documentation search
- 02Paginated Markdown page retrieval
- 03Public documentation space listings
- 04Links to original documentation pages
Use cases
- 01Check CAN frame formats before integration
- 02Find product manuals and firmware notes
- 03Look up chassis troubleshooting steps
MCP support
Exposes four read-only tools over Streamable HTTP: search_docs, get_doc, list_docs, and list_spaces. MCP clients can query public AgileX documentation and follow source URLs.
Configuration
Remote servers need no local install. Pick your client, then copy the config or install in one click.
https://service.agilex.ai/agilex-docs/mcpclaude mcp add --transport http ai-agilex-service-docs https://service.agilex.ai/agilex-docs/mcp{"mcpServers":{"ai-agilex-service-docs":{"type":"http","url":"https://service.agilex.ai/agilex-docs/mcp"}}}Open in Cursor{"servers":{"ai-agilex-service-docs":{"type":"http","url":"https://service.agilex.ai/agilex-docs/mcp"}}}Open in VS Code{"mcpServers":{"ai-agilex-service-docs":{"type":"http","url":"https://service.agilex.ai/agilex-docs/mcp"}}}{"mcpServers":{"ai-agilex-service-docs":{"serverUrl":"https://service.agilex.ai/agilex-docs/mcp"}}}Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.
Tools
Details
From the project READMEAGILEX Docs MCP
Official product documentation for AgileX Robotics (松灵机器人) — user manuals,
CAN 2.0B protocol references, firmware notes, SDK tech posts and after-sales FAQ for
piper, pika, nero, ranger, limo, scout, bunker, hunter, tracer,
umr, cobot_magic and aloha.
Point your AI coding assistant at this server before writing integration code for AgileX hardware, so it consults the real manual instead of guessing baud rates, frame formats or pinouts.
This repository is the public contract, not the implementation. It documents the endpoint, the tool signatures and every client configuration. The indexing service itself stays private, the same way Cloudflare, Sentry and Linear publish their remote MCP servers.
Endpoint
| MCP URL | https://service.agilex.ai/agilex-docs/mcp |
| Transport | Streamable HTTP — single endpoint, stateless |
| Protocol | 2025-11-25 (also answers 2025-06-18, 2025-03-26, 2024-11-05) |
| Auth | None. Read-only public docs, rate limited per IP |
| Registry | ai.agilex.service/docs |
| Docs page | https://service.agilex.ai/agilex-docs/ |
| Health | https://service.agilex.ai/agilex-docs/health |
No API key, no OAuth, no local process. If your client speaks Streamable HTTP, you only need the URL.
Quick start
# Claude Code
claude mcp add --transport http agilex-docs https://service.agilex.ai/agilex-docs/mcp
# Codex CLI (writes ~/.codex/config.toml)
codex mcp add agilex-docs --url https://service.agilex.ai/agilex-docs/mcp
Cursor — one click:
cursor://anysphere.cursor-deeplink/mcp/install?name=agilex-docs&config=eyJ1cmwiOiJodHRwczovL3NlcnZpY2UuYWdpbGV4LmFpL2FnaWxleC1kb2NzL21jcCJ9
Any client that reads mcpServers (Claude Desktop, Cline, Windsurf, Cherry Studio,
Continue, Zed, LibreChat, Dify …):
{
"mcpServers": {
"agilex-docs": {
"url": "https://service.agilex.ai/agilex-docs/mcp"
}
}
}
Full per-client instructions: docs/CLIENTS.md.
Tools
Four read-only tools. The names are deliberately verb_noun so a model can pick
the right one without reading the schema first.
| Tool | Purpose | Parameters |
|---|---|---|
search_docs | Full-text search. Start here. Locate before reading. | query (include the product name), limit (1–25, default 8), space (optional) |
get_doc | Read one page as Markdown, paginated | doc_id, max_chars (default 20 000, max 120 000), offset |
list_docs | Inventory of a single space | space (optional), limit (1–300, default 50), offset |
list_spaces | All public spaces with page counts | — |
search_docs returns doc_id, title, space, url, score, chars and a
snippet. Feed doc_id into get_doc. If the response has truncated: true,
call get_doc again with next_offset.
Response shape
// search_docs("piper CAN 波特率")
{
"query": "piper CAN 波特率",
"count": 3,
"results": [
{
"doc_id": "01a06659-2d4e-7029-bc64-63f9352b34a6",
"title": "PIPER X 用户手册(CN)",
"space": "AGX-机械臂产品手册",
"url": "https://kb.agilex.ai/s/agx-robot-arm-products-cn-en/p/pWVjLJsYc0",
"score": 18.42,
"chars": 13264,
"snippet": "...CAN通信标准采用的是CAN2.0B标准,通讯波特率为1000K..."
}
]
}
// get_doc(doc_id="01a06659-…", max_chars=2000)
{
"doc_id": "01a06659-2d4e-7029-bc64-63f9352b34a6",
"title": "PIPER X 用户手册(CN)",
"url": "https://kb.agilex.ai/s/agx-robot-arm-products-cn-en/p/pWVjLJsYc0",
"chars": 13264,
"offset": 0,
"truncated": true,
"next_offset": 2000,
"content": "..."
}
url always points at the original Docmost page — cite it so the user can verify.
Client configuration
Cursor
.cursor/mcp.json in the project, or ~/.cursor/mcp.json globally:
{
"mcpServers": {
"agilex-docs": {
"url": "https://service.agilex.ai/agilex-docs/mcp"
}
}
}
Reload the window (Ctrl+Shift+P → Reload Window). Settings → MCP should list
agilex-docs with 4 tools.
Claude Code
# all projects
claude mcp add --transport http agilex-docs https://service.agilex.ai/agilex-docs/mcp
# this project only (writes .mcp.json, can be committed)
claude mcp add --scope project --transport http agilex-docs https://service.agilex.ai/agilex-docs/mcp
claude mcp list
Codex CLI
codex mcp add agilex-docs --url https://service.agilex.ai/agilex-docs/mcp
or ~/.codex/config.toml:
[mcp_servers.agilex-docs]
url = "https://service.agilex.ai/agilex-docs/mcp"
Inside Codex, /mcp lists active servers. Codex uses the server's instructions
field as global guidance, so the search-then-read workflow is already in place.
DeepSeek Harness (DSH)
DSH connects through @deepseek-ai/dsh-mcp-client, configured as a Cordis overlay:
- insert:
- id: agilex-docs
name: '@deepseek-ai/dsh-mcp-client'
config:
serverName: agilex-docs
transport: streamable-http
url: https://service.agilex.ai/agilex-docs/mcp
dsh web --patch "$PWD/examples/agilex-docs.cordis.yml"
Tools appear as mcp__agilex-docs__search_docs.
Claude Desktop (stdio bridge)
{
"mcpServers": {
"agilex-docs": {
"command": "npx",
"args": ["-y", "mcp-remote", "https://service.agilex.ai/agilex-docs/mcp"]
}
}
}
Quit and reopen the app completely after saving.
VS Code / Copilot
.vscode/mcp.json — note the top-level key here is servers, not mcpServers:
{
"servers": {
"agilex-docs": {
"type": "http",
"url": "https://service.agilex.ai/agilex-docs/mcp"
}
}
}
Or Ctrl+Shift+P → MCP: Add Server → HTTP → paste the URL.
Cherry Studio
Settings → MCP Servers → Add → type streamableHttp, URL as above.
Cherry Studio also accepts the mcpServers JSON directly.
ChatGPT custom connector
Paid plan, web only: Settings → Connectors → Advanced → enable Developer mode → Create → URL above, authentication No authentication.
Example prompts
I need a CAN control script for the piper arm. First call
search_docswith "piper CAN 报文", thenget_docon the best hit, and write the code using the frame format and baud rate from the manual. Cite the manual URL in a comment.
Our ranger mini throws a chassis error code. Search the after-sales FAQ for the code, quote the troubleshooting steps and link the page.
Because the server ships an instructions block telling the model to search first
and cite URLs, the workflow usually happens without any extra prompting.
Scope and data
The corpus is built from Docmost spaces marked 「互联网所有人可访问」 — already public at https://kb.agilex.ai. Spaces marked 内部 / 非对外 are not reachable: the crawler only uses Docmost's anonymous share endpoints and never authenticates, so internal content cannot leak even through a bug.
| Pages | 346 |
| Spaces | 26 |
| Characters | ~3.0 M |
| Refresh | daily 05:20 Asia/Shanghai |
| Languages | Chinese and English |
New public spaces appear automatically; revoked shares drop out on the next sync.
Rate limits
| Scope | Limit |
|---|---|
| Per IP, per minute | 60 requests |
| Per IP, per day | 3 000 requests |
| Over limit | HTTP 429 + Retry-After |
Higher quota or a dedicated endpoint: contact AgileX (see Feedback).
Limits
- Read-only. No write tools; nothing here can move a robot.
- Images are not inlined. Docmost signs attachment URLs with a short TTL, so a
snapshot would ship dead links. Images render as
(图:caption); open the pageurlto view them. - Binary attachments (PDF/XLSX) in public spaces are not parsed — page bodies only.
- Lexical matching, not semantic. BM25 + CJK bigrams. Rephrase if a term misses.
- One product family per query works best; cross-product questions need multiple searches.
Verify it works
# health
curl -s https://service.agilex.ai/agilex-docs/health | jq
# MCP handshake
curl -s -X POST https://service.agilex.ai/agilex-docs/mcp \
-H 'Content-Type: application/json' \
-H 'Accept: application/json, text/event-stream' \
-d '{"jsonrpc":"2.0","id":1,"method":"initialize","params":{"protocolVersion":"2025-06-18","capabilities":{},"clientInfo":{"name":"curl","version":"1"}}}' | jq
# full round trip (initialize → tools/list → tools/call)
./scripts/smoke-test.sh
Repository layout
README.md this file
server.json official MCP Registry manifest
LICENSE MIT (documentation + manifest)
docs/CLIENTS.md per-client setup, long form
examples/ copy-paste configs per client
scripts/smoke-test.sh end-to-end check against the live endpoint
Feedback
Missing or wrong document → contact AgileX support through https://www.agilex.ai/ and include the page URL.
Issues about this repository (manifest, docs, client configs) → open an issue here. Issues about document content → the support channel, since the docs live in the internal knowledge base and this repo cannot edit them.
License
MIT — see LICENSE. The license covers the documentation and manifest in this repository. The documentation content served over MCP remains the property of AgileX Robotics.
Comments
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From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.