[BUG] search_knowledge_base_retrieve tool does not offer certain API options

### Describe the bug

(This may be an enhancement request and not a bug...)

When running a query of the `search_knowledge_base_retrieve` tool, you get back this response:

```
{
"result": {
"tools": [
{
"name": "search_knowledge_base_retrieve",
"description": "Execute a retrieval operation using a specific Azure AI Search knowledge base, effectively searching and querying the underlying\ndata sources as needed to find relevant information. Provide either a --query for single-turn retrieval or one or more\nconversational --messages in role:content form (e.g. user:What policies apply?). Specifying both --query and --messages is not\nallowed.\n\nRequired arguments:\n- service\n- knowledge-base",
"inputSchema": {
"type": "object",
"properties": {
"tenant": {
"type": "string",
"description": "The Microsoft Entra ID tenant ID or name. This can be either the GUID identifier or the display name of your Entra ID tenant."
},
"auth-method": {
"type": "integer",
"description": "Authentication method to use. Options: 'credential' (Azure CLI/managed identity), 'key' (access key), or 'connectionString'."
},
"retry-delay": {
"type": "number",
"description": "Initial delay in seconds between retry attempts. For exponential backoff, this value is used as the base."
},
"retry-max-delay": {
"type": "number",
"description": "Maximum delay in seconds between retries, regardless of the retry strategy."
},
"retry-max-retries": {
"type": "integer",
"description": "Maximum number of retry attempts for failed operations before giving up."
},
"retry-mode": {
"type": "integer",
"description": "Retry strategy to use. 'fixed' uses consistent delays, 'exponential' increases delay between attempts."
},
"retry-network-timeout": {
"type": "number",
"description": "Network operation timeout in seconds. Operations taking longer than this will be cancelled."
},
"service": {
"type": "string",
"description": "The name of the Azure AI Search service (e.g., my-search-service)."
},
"knowledge-base": {
"type": "string",
"description": "The name of the knowledge base within the Azure AI Search service."
},
"query": {
"type": "string",
"description": "Natural language query for retrieval when a conversational message history isn't provided."
},
"messages": {
"type": "array",
"description": "Conversation history messages passed to the knowledge base. Able to specify multiple --messages entries. Each entry formatted as role:content, where role is `user` or `assistant` (e.g., user:How many docs?).",
"items": {
"type": "string"
}
}
},
"required": [
"service",
"knowledge-base"
]
},
"annotations": {
"title": "Execute retrieval using a knowledge base in Azure AI Search",
"destructiveHint": false,
"idempotentHint": true,
"openWorldHint": true,
"readOnlyHint": true
}
}
]
},
"id": 1,
"jsonrpc": "2.0"
}
```

This schema structure doesn't offer any options for getting back citation / reference information, which is fairly critical functionality for any type of RAG implementation.

In order to get back citation / references, you must pass along these attributes to the knowledge base retrieval API endpoint ([API reference](https://learn.microsoft.com/en-us/rest/api/searchservice/knowledge-retrieval/retrieve?view=rest-searchservice-2025-11-01-preview&tabs=HTTP#searchindexknowledgesourceparams), [Agentic Retrieval Example](https://github.com/MicrosoftDocs/azure-ai-docs/blob/main/articles/search/agentic-retrieval-how-to-retrieve.md#set-references-for-each-knowledge-source)):

```
"knowledgeSourceParams": [
{
"knowledgeSourceName": "knowledgesource-name",
"includeReferences": true,
"includeReferenceSourceData": true,
"alwaysQuerySource": false,
"kind": "searchIndex"
}
]
```

Can this tool be updated to support these parameters?

Thanks!

J.C.

### Expected behavior

When running a query of the `search_knowledge_base_retrieve` tool, you should get back `knowledgeSourceParams` in the `inputSchema` property.

### Actual behavior

`knowledgeSourceParams` is not present in the `inputSchema` property.

### Reproduction Steps

(the below does not include the Entra ID or Azure resource configuration)

Using Docker, you can fire up a local MCP server as such (customize as required):

`docker run --rm -it -p 8080:8080 -e ASPNETCORE_ENVIRONMENT=Dev -e ASPNETCORE_URLS=http://+:8080 -e AZURE_MCP_DANGEROUSLY_DISABLE_HTTPS_REDIRECTION=true -e AZURE_MCP_COLLECT_TELEMETRY=false -e AzureAd__Instance=https://login.microsoftonline.com/ -e AzureAd__TenantId=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -e AzureAd__ClientId=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -e AZURE_TENANT_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -e AZURE_CLIENT_ID=xxxxxxxx-xxxx-xxxx-xxxx-xxxxxxxxxxxx -e AZURE_CLIENT_SECRET=secret_value mcr.microsoft.com/azure-sdk/azure-mcp:2.0.0-beta.19-amd64 --transport http --outgoing-auth-strategy UseHostingEnvironmentIdentity --mode single --read-only --tool search_knowledge_base_retrieve`

You can then call it via PowerShell like this:

```
$Token = 'token_value'
$Headers = @{ 'Authorization' = ('Bearer {0}' -f $Token); 'Content-Type' = 'application/json'; 'Accept' = 'application/json, text/event-stream' }
$BodyListTools = @{ 'jsonrpc' = '2.0'; 'id' = 1; 'method' = 'tools/list'; 'params' = @{} } | ConvertTo-Json
$McpResponseListTools = Invoke-WebRequest -Method Post -Uri 'http://localhost:8080/' -Headers $Headers -Body $BodyListTools
```

This will result in a response similar to:

```
{
"result": {
"tools": [
{
"name": "search_knowledge_base_retrieve",
"description": "Execute a retrieval operation using a specific Azure AI Search knowledge base, effectively searching and querying the underlying\ndata sources as needed to find relevant information. Provide either a --query for single-turn retrieval or one or more\nconversational --messages in role:content form (e.g. user:What policies apply?). Specifying both --query and --messages is not\nallowed.\n\nRequired arguments:\n- service\n- knowledge-base",
"inputSchema": {
"type": "object",
"properties": {
"tenant": {
"type": "string",
"description": "The Microsoft Entra ID tenant ID or name. This can be either the GUID identifier or the display name of your Entra ID tenant."
},
"auth-method": {
"type": "integer",
"description": "Authentication method to use. Options: 'credential' (Azure CLI/managed identity), 'key' (access key), or 'connectionString'."
},
"retry-delay": {
"type": "number",
"description": "Initial delay in seconds between retry attempts. For exponential backoff, this value is used as the base."
},
"retry-max-delay": {
"type": "number",
"description": "Maximum delay in seconds between retries, regardless of the retry strategy."
},
"retry-max-retries": {
"type": "integer",
"description": "Maximum number of retry attempts for failed operations before giving up."
},
"retry-mode": {
"type": "integer",
"description": "Retry strategy to use. 'fixed' uses consistent delays, 'exponential' increases delay between attempts."
},
"retry-network-timeout": {
"type": "number",
"description": "Network operation timeout in seconds. Operations taking longer than this will be cancelled."
},
"service": {
"type": "string",
"description": "The name of the Azure AI Search service (e.g., my-search-service)."
},
"knowledge-base": {
"type": "string",
"description": "The name of the knowledge base within the Azure AI Search service."
},
"query": {
"type": "string",
"description": "Natural language query for retrieval when a conversational message history isn't provided."
},
"messages": {
"type": "array",
"description": "Conversation history messages passed to the knowledge base. Able to specify multiple --messages entries. Each entry formatted as role:content, where role is `user` or `assistant` (e.g., user:How many docs?).",
"items": {
"type": "string"
}
}
},
"required": [
"service",
"knowledge-base"
]
},
"annotations": {
"title": "Execute retrieval using a knowledge base in Azure AI Search",
"destructiveHint": false,
"idempotentHint": true,
"openWorldHint": true,
"readOnlyHint": true
}
}
]
},
"id": 1,
"jsonrpc": "2.0"
}
```

You can then further call the actual tool with a real question. You will get back an answer, but it will not include the citation / reference information.

### Environment

Cloud: Azure Commercial
Resource: Azure AI Search
Running locally via Docker Desktop.
Image: mcr.microsoft.com/azure-sdk/azure-mcp:2.0.0-beta.19-amd64