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docs(mcp): document embedding_batch_size for semantic tool filter#512

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litellm_mcp_semantic_filter_embedding_batch_size
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docs(mcp): document embedding_batch_size for semantic tool filter#512
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litellm_mcp_semantic_filter_embedding_batch_size

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Summary

Documents the new embedding_batch_size option on mcp_semantic_tool_filter, which caps how many tool descriptions go into each embedding request when building the semantic index. It defaults to 1024 and exists so large tool catalogs no longer produce a single oversized embedding call that hangs or errors against providers with input-array limits (DeepInfra 1024, OpenAI 2048)

Companion to the code fix in BerriAI/litellm#32534 (issue BerriAI/litellm#32528). Adds the option to the config example and the options list in docs/mcp_semantic_filter.md

Link to Devin session: https://app.devin.ai/sessions/1e4d26977e4a4820b821b56b1d3e0d70

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