feat: refactor node spec and add mcp tools (#244)

* refactor: carve out extraction panel

* refactor: create spec versions for node types

* refactor: create a GenericNode and remove custom nodes

* feat: add python and typescript sdk

* add dograh sdk

* fix: fetch draft workflow definition over published one

* fix: fix routes of SDKs to use code gen

* chore: remove doclink dependency to reduce image size

* chore: format files

* chore: bump pipecat

* feat: let mcp fetch archived workflows on demand

* chore: fix tests

* feat: add sdk documentation

* chore: change banner and add badge

docs/integrations/mcp.mdx

@@ -16,6 +16,16 @@ Dograh exposes an [MCP (Model Context Protocol)](https://modelcontextprotocol.io
 
 The endpoint is also shown in **Platform Settings → MCP Server** inside the Dograh UI.
 
+<Note>
+If you deployed Dograh to a remote server using [`setup_remote.sh`](/deployment/docker#option-2%3A-remote-server-deployment), your endpoint is served with a self-signed SSL certificate. Claude Code will refuse MCP connections to it unless you start the CLI with TLS verification disabled:
+
+```bash
+NODE_TLS_REJECT_UNAUTHORIZED=0 claude
+```
+
+This is only required for self-signed certificates. If you have set up a [custom domain](/deployment/custom-domain) with Let's Encrypt certificates via Certbot, no extra flag is needed.
+</Note>
+
 ## Claude Code
 
 Register Dograh as an MCP server with the Claude Code CLI:
@@ -56,14 +66,33 @@ Restart Claude Desktop after saving. The Dograh tools should appear in the tool
 
 Any MCP client that supports Streamable HTTP transport can connect with the same URL and header. Paste the configuration above into your client's MCP settings file and replace `YOUR_API_KEY`.
 
-## Available tools
+## Example prompts
 
-Once connected, your AI assistant can:
+Once the MCP server is connected, you can drive Dograh from your coding agent in plain English. A few prompts to try:
 
-- `list_workflows` — list agents in your workspace
-- `get_workflow` — fetch an agent's definition by ID
-- `search_dograh_docs` — search Dograh documentation
-- `fetch_dograh_doc` — retrieve a specific doc page
+**Explore your workspace**
+
+- "List my agents in Dograh."
+- "Show me the definition of the agent called *Lead Qualifier*."
+- "Which credentials and tools are configured in my Dograh workspace?"
+- "List the recordings from my most recent agent."
+
+**Edit an agent**
+
+- "In my *Lead Qualifier* agent, add a new agent node after the greeting that asks the caller for their budget, then routes to the existing qualification node."
+- "Add an end-call node to *Support Bot* that triggers when the user says they are done, with a polite goodbye prompt."
+- "Rename the *intro* node in *Lead Qualifier* to *greeting* and update any edges that reference it."
+- "Change the LLM model on all agent nodes in *Support Bot* to `gpt-4o-mini`."
+
+**Learn the platform**
+
+- "Search the Dograh docs for how to configure a TURN server."
+- "What node types does Dograh support, and what fields does a `knowledge_base` node take?"
+- "How do I deploy Dograh on a custom domain with HTTPS?"
+
+<Note>
+Agent edits are saved as a new **draft** version — your published agent keeps serving calls until you explicitly publish the draft from the Dograh UI.
+</Note>
 
 <Note>
 The API key controls which workspace the assistant sees. Treat it like any other credential — do not commit it to source control or paste it into shared chats.