feat: add MCP tools caching to list_mcp_tools - #276
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| def _make_cache_key(filter: MCPToolFilter | None, user_scoped: bool) -> str: |
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Shouldn’t we create this cache key based on some user properties? @NicoleMGomes, any thoughts about it?
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Adds optional in-process result caching for list_mcp_tools() to avoid redundant MCP session round-trips in agentic loops where the tool list rarely changes. - New CacheOptions(ttl, max_size) dataclass accepted by list_mcp_tools(cache=...) - Results cached per filter + auth-type combination with monotonic TTL (default 600 s) - cache.evict() for caller-triggered invalidation - LRU eviction when max_size entries exceeded (default 32) - 19 new unit tests covering hit/miss, TTL expiry, LRU eviction, evict() - user-guide.md updated with usage examples and CacheOptions API reference Closes SAP#178
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Description
Adds optional in-process result caching for
list_mcp_tools()to avoid redundant MCP session round-trips in agentic loops where the tool list rarely changes.CacheOptions(ttl, max_size)dataclass — pass tolist_mcp_tools(cache=...)cache.evict()for caller-triggered invalidation when tools change on the servermax_sizeentries exceeded (default 32) — prevents unbounded memory growthuser-guide.mdupdated with usage examples andCacheOptionsAPI referenceRelated Issue
Closes #178
Type of Change
How to Test
uv syncuv run pytest tests/agentgateway/unit/test_tools_cache.py -vuv run pytest tests/agentgateway/unit/ -qChecklist
Additional Notes
Cache is in-process only — not shared across client instances, processes, or Kubernetes pods. This matches the existing
_TokenCachedesign. Concurrent cache misses produce redundant fetches but no data corruption (same accepted trade-off documented in_token_cache.py).This PR was implemented with AI assistance (Claude) per the SAP GenAI contribution guidelines.