Troubleshooting and FAQ
An MCP server won't connect or its tools aren't called
Discovery fails, tools don't appear, or the agent never calls them. Transport, address, auth and timeout checks.
Troubleshooting2 min readUpdated 23 October 2026
SentientOne calls MCP servers from the cloud over HTTP, one POST per JSON-RPC call (initialize, then tools/list and tools/call). Most connection problems come from a server that isn't reachable from the internet, a transport that isn't supported, or missing credentials.
Check these in order
- 1
It's not a stdio server
Servers that run as a local process (stdio) can't be called from the cloud. Run the server behind an HTTP endpoint, or use one that offers streamable HTTP.
- 2
It answers HTTP POST
The server must accept JSON-RPC over POST and answer in JSON or an event-stream body. The older SSE transport (a GET stream plus a separate POST address) isn't supported. If your URL has no path, discovery also tries it with
/mcpadded. - 3
It's on a public address
Private, loopback, link-local and other non-public addresses are refused, and so is
localhost. Redirects aren't followed. Use the server's public URL. See MCP network rules. - 4
The auth matches
Choose the auth the server expects: none, a bearer token (
Authorization: Bearer …), an API key in a header you name, or basic. Add any other headers it needs. See MCP authentication. - 5
It answers within the time limits
Discovery waits 10 seconds per call. During a chat, each tool call has 10 seconds. Slow tools fail and the agent carries on without them.
- 6
The tool list is fresh
Tools are discovered when you add or test the server, and saved with the agent, so chats never wait on discovery. After adding tools to your server, run discovery again on the agent's Tools tab.
- 7
The model knows when to use it
The model decides from the tool's name, description and input schema. Give tools clear descriptions, and tell the agent in its prompt when to use them.
More questions
Where do I see what the tool returned?
In the stream (tool_call and tool_result events), next to each reply in the Playground, and as tool.execute spans in the trace.
The tool's output seems cut off
The model sees at most 2,500 characters of a tool's output. Return compact results.
The agent calls tools over and over
A reply can use up to 8 tool rounds, and repeating the same call with the same arguments is skipped. Tighten the tool descriptions and the prompt.
Does SentientOne itself expose an MCP server?
No. SentientOne calls your MCP servers; to reach SentientOne from your code, use the REST API.
Still stuck?
Email us with what you tried and any request id. A person replies.