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docs: troubleshooting mcp tools component missing tool mode (#11381)
* mcp-tool-mode-missing * Apply suggestions from code review Co-authored-by: April I. Murphy <36110273+aimurphy@users.noreply.github.com> --------- Co-authored-by: April I. Murphy <36110273+aimurphy@users.noreply.github.com>
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@ -13,6 +13,10 @@ To do this, use the **MCP Tools** component's [HTTP/SSE mode](/mcp-client#mcp-ht
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For more information, see [Use Langflow as an MCP client](/mcp-client) and [Use Langflow as an MCP server](/mcp-server).
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:::tip Tool mode is missing
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If you're upgrading an existing flow and the **MCP Tools** component loses its **Tool Mode** option, see [MCP Tools component loses Tool Mode option after upgrading flows](/troubleshoot#mcp-tools-component-loses-tool-mode-option-after-upgrading-flows).
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:::
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## MCP Tools parameters
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| Name | Type | Description |
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@ -316,6 +316,25 @@ To work around this issue, run the server and host in the same operating environ
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Alternatively, configure Langflow Desktop to accept connections from WSL at the default Windows IP address of `10.255.255.254:7860` instead of `localhost`.
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### MCP Tools component loses Tool Mode option after upgrading flows {#mcp-tools-component-loses-tool-mode-option-after-upgrading-flows}
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If you upgrade an existing flow that uses the [**MCP Tools** component](/mcp-tools) in **Tool Mode**, the component might lose its **Tool Mode** setting after upgrading the flow.
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This can break flows that rely on the component's **Tool Mode** to expose MCP tools to agents.
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If you experience this when upgrading a flow that you created in Langflow version 1.7.1 or earlier, do the following:
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1. Select the **MCP Tools** component in your flow.
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2. Click <Icon name="Code" aria-hidden="true"/> **Code** to open the component's code editor.
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3. In the component's template structure, locate the `tool_mode` field under `inputs`.
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The field can be either missing or set to `false`.
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4. Add the `tool_mode` field if it's missing, and set it to `true`:
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```python
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tool_mode = True
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```
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5. Click **Check & Save** to apply the code changes.
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## Token length limit errors in Embedding Model components
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Token length errors can happen if your chunking strategy doesn't align with your embedding model's tokenization limits.
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