[mcp-analysis] MCP Structural Analysis - 2026-08-19 #53988
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This discussion has been marked as outdated by GitHub MCP Structural Analysis. A newer discussion is available at Discussion #54223. |
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MCP structural analysis of 9 representative GitHub tool calls against
github/gh-aw(plus the injected workflow-context block). Average usefulness for agentic work: 3.3/5. The clearest pattern: nearly every raw GitHub MCP tool response repeats a ~1.4KB base64-encoded PNG icon pair inside_meta.serverInfoon every single call — pure overhead unrelated to the requested data, and it dominates small responses likeget_label(over 90% of the payload). The custommcpscriptswrapper forlist_workflowsavoids this entirely and was the cleanest response observed alongside the injected<github-context>block.Full Structural Analysis Report
Executive Summary
github_context,list_workflows(wrapper) — 5/5list_issues,get_label— 2/5Usefulness Ratings for Agentic Work
perPage, no bloatfieldsfiltering, useful head/base SHAsfieldsfiltering keeps items minimal; icon overhead still presentSchema Analysis
content/resourcerule.helpis a full markdown essay per alert_metafieldsis passed_metabloatResponse Size Analysis
Tool-by-Tool Analysis
_metafieldsfilterrule.helpper item_metaoverhead_meta>90% of payload_metaoverheadperPage30-Day Trend Summary
Recommendations
github_context(injected, free),list_workflowsvia themcpscriptswrapper,list_pull_requestswith explicitfields.list_issues(make redaction reasons visible/actionable instead of a bare count),get_label(the per-call_meta.serverInfoicon payload should not be repeated on every response — it's static server metadata, not per-request data).github_context,list_workflows(wrapper).get_file_contentsonREADME.md(auto-generated contributor list) andlist_code_scanning_alerts(verbose per-alerthelptext) — both would benefit from an optional "compact" response mode for agentic callers who only need actionable fields._meta.serverInfoadds a fixed ~350-token tax to almost every call regardless of payload size, which is proportionally worst for small, high-value queries likeget_labelandlist_discussionswith smallperPage.Visualizations
Charts could not be generated this run —
pip install pandas/matplotlib/seabornhas no route to PyPI under the workflow's network restrictions. This will be revisited in a future run; the raw CSV-equivalent JSONL data is retained in cache-memory (/tmp/gh-aw/cache-memory/mcp_analysis.jsonl) for the next run to pick up and chart once a 30-day window has accumulated.All reactions