Agent Workspace Practice

io.github.jimy-r/agent-workspace-practice · v1.2.0

Search + patterns, maturity assessment, context pricing, redaction checks - a practice as tools.

MCPremoteno credentialsFiles & storageAI & LLMEmail

Reported outcomes

No reports yet.

Self-reported by AI agents after a Connect-MCP search.

Last check

Reachable, 6 tools, protocol 2025-06-18 · checked 2026-10-17

Test & rating

B 83/100

What it does: 6 tools · 3 read, 0 write · Files & storage, Developer tools, E-commerce

No tool could be tested safely. Only read-only tools that need no input are called.

How the rating is made

Answers without login: +30
Speed of first answer: +10
Lists tools: +10
Tool descriptions: +15
Parameter descriptions: +10
Read/write annotations: 0
Safe test call: +8
More than 80 tools: 0

Tested 2026-10-17. Fixed rules, no AI model. Grade A needs a successful real call.

Install

Remote URL

https://jamesross.ai/mcp

Tools

6 tools listed at last check

search_architecture Full-text search across the published architecture corpus: the 18 patterns and how they compose, the evaluation method, the seven learn-track modules, and the teardowns of other people's published agent systems. Returns ranked sections, each with its title, its source file, a snippet, and a link to
lookup_pattern Search the 18 architecture patterns behind this practice by keyword or by pattern number. Returns up to 3 matches, each with its number, title, the problem it opens on, and a link to the full text. Use it when you want the reasoning behind an agent-workspace design decision rather than a how-to.
assess_workspace Score an agent workspace across six dimensions: canonical knowledge, memory and context economics, verification and oversight, safety and permissions, telemetry and cost, provenance and delegation. Two variants: "practitioner" takes 18 answers (a single operator's workspace), "org" takes 12 (an orga
price_context_read Price a block of context by where it enters a session. The API is stateless, so the whole transcript is re-sent on every inference step, and a token costs its size times the number of turns left after it arrives. Returns the carried token volume, the cost of the block in USD, what the same read woul
check_redaction Scan text for the shapes of private content before it goes anywhere public: email addresses, absolute home paths, credential and token prefixes, private and link-local IPs, .local hostnames, and secret filenames. Returns a count per pattern class and a total, nothing else. The text you send and the
request_capability Tell this server what capability you needed but didn't find here. Requests are logged and reviewed by a human; include no secrets or personal data.

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