Context makes the Coworker: Glean preferred ~2.5x as often as off-the-shelf MCP tools, which consumed 30% more tokens in Claude Cowork

This post benchmarks Glean's centralized indexing and knowledge graph-based MCP server against federated, off-the-shelf MCP tools using Claude Cowork. It quantifies that Glean was preferred ~2.5x more often and consumed ~30% fewer tokens. The analysis highlights the 'federated search token tax' and the economic trade-offs between upfront data storage costs (indexing) and climbing compute costs (token consumption). It details the evaluation design, metrics (utility, correctness, completeness, tool fidelity), and provides three query examples illustrating the superiority of Glean's context layer in generating work-ready outputs across various task complexities.