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fix reference to filter type

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Adil Hafeez 2025-12-23 16:22:03 -08:00
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3
docs/source/concepts/filter_chain.rst
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@ -52,9 +52,10 @@ Filter Chain Programming Model (HTTP and MCP)
Filters are implemented as simple RESTful endpoints reachable via HTTP. If you want to use the `Model Context Protocol (MCP) <https://modelcontextprotocol.io/>`_, you can configure that as well, which makes it easy to write filters in any language. However, you can also write a filter as a plain HTTP service.
When defining a filter in Plano configuration, the following fields are optional:
* ``type``: Controls the filter runtime (defaults to ``mcp``). You can also set this to ``rest`` for plain HTTP filters.
* ``type``: Controls the filter runtime. Use ``mcp`` for Model Context Protocol filters, or ``http`` for plain HTTP filters. Defaults to ``mcp``.
* ``transport``: Controls how Plano talks to the filter (defaults to ``streamable-http`` for efficient streaming interactions over HTTP). You can omit this for standard HTTP transport.
* ``tool``: Names the MCP tool Plano will invoke (by default, the filter ``id``). You can omit this if the tool name matches your filter id.

6
docs/source/guides/prompt_guard.rst
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@ -21,11 +21,13 @@ more reliable, and easier to reason about.
- **Domain and Topicality Enforcement**: Ensure that agents only respond to prompts within an approved domain (for example, finance-only or healthcare-only use cases) and reject unrelated queries.
- **Dynamic Error Handling**: Provide clear error messages when requests violate policy, helping users correct their inputs.
How Guardrails Work
-------------------
In Plano, guardrails are implemented as MCP filters that validate incoming requests. Each filter receives the chat messages, evaluates them
against policy, and either lets the request continue or raises a ``ToolError`` to reject it with a helpful error message.
Guardrails can be implemented as either in-process MCP filters or as HTTP-based filters. HTTP filters are external services that receive the request over HTTP, validate it, and return a response to allow or reject the request. This makes it easy to use filters written in any language or run them as independent services.
Each filter receives the chat messages, evaluates them against policy, and either lets the request continue or raises a ``ToolError`` (or returns an error response) to reject it with a helpful error message.
The example below shows an input guard for TechCorp's customer support system that validates queries are within the company's domain: