/devops/disk-ops — liz's doc public knowledge MCP Resource
/devops/disk-ops
is one of 101 resources on the
liz's doc public knowledge
MCP server. Connect the server and your client can attach it as context.
by client
How to attach /devops/disk-ops from your client
- Claude Code liz's doc public knowledge Resource//devops/disk-ops run in your project directory
- Claude Desktop liz's doc public knowledge Resource//devops/disk-ops ~/Library/Application Support/Claude/claude_desktop_config.json
- Cursor liz's doc public knowledge Resource//devops/disk-ops ~/.cursor/mcp.json
- VS Code liz's doc public knowledge Resource//devops/disk-ops .vscode/mcp.json
- Zed liz's doc public knowledge Resource//devops/disk-ops ~/.config/zed/settings.json
- Windsurf liz's doc public knowledge Resource//devops/disk-ops ~/.codeium/windsurf/mcp_config.json
- Cline liz's doc public knowledge Resource//devops/disk-ops ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json
- Gemini CLI liz's doc public knowledge Resource//devops/disk-ops ~/.gemini/settings.json
- Grok liz's doc public knowledge Resource//devops/disk-ops .mcp.json (in your project root)
- ChatGPT liz's doc public knowledge Resource//devops/disk-ops Settings → Connectors → Advanced → Developer mode
- Claude.ai liz's doc public knowledge Resource//devops/disk-ops Settings → Connectors → Add custom connector
- LangChain liz's doc public knowledge Resource//devops/disk-ops pip install langchain-mcp-adapters
Other resources on this server
- docs-explorer
- /
- /00-start-here
- /ai/00-learning-path
- /ai/01-model-foundations/01-tokens-and-sampling
- /ai/01-model-foundations/02-attention-and-moe
- /ai/01-model-foundations/03-inference-and-kv-cache
- /ai/01-model-foundations/04-reasoning-and-verification
- /ai/02-context-and-interfaces/01-prompt-and-output-contracts
- /ai/02-context-and-interfaces/02-context-engineering
- /ai/02-context-and-interfaces/03-retrieval-and-evidence
- /ai/03-agent-systems/01-agent-loop
- /ai/03-agent-systems/02-tools-and-mcp
- /ai/03-agent-systems/03-skills-and-task-context
- /ai/03-agent-systems/04-memory-and-recovery
- /ai/03-agent-systems/05-authority-and-tool-boundaries
- /ai/03-agent-systems/06-multi-agent-orchestration
- /ai/04-evaluation-and-production/01-evaluation-and-observability
- /ai/04-evaluation-and-production/02-cost-performance-and-reliability
- /ai/04-evaluation-and-production/03-release-and-recovery
- /compilers/00-learning-path
- /compilers/01-lexical-analysis/01-regular-expressions-and-automata
- /compilers/01-lexical-analysis/02-lexer-design
- /compilers/02-syntax-analysis/01-recursive-descent-and-ll-analysis
- /compilers/02-syntax-analysis/02-lr-parsing
- /compilers/02-syntax-analysis/03-ast-design-and-error-recovery
- /compilers/03-semantic-analysis/01-symbol-tables-and-scopes
- /compilers/03-semantic-analysis/02-type-systems
- /compilers/04-intermediate-representation/01-ssa-form
- /compilers/04-intermediate-representation/02-llvm-ir-in-practice
- /compilers/05-optimization/01-data-flow-analysis
- /compilers/05-optimization/02-classic-optimizations
- /compilers/05-optimization/03-register-allocation
- /compilers/06-code-generation/01-instruction-selection
- /compilers/06-code-generation/02-target-code-and-abi
- /compilers/07-runtime/01-garbage-collection
- /compilers/07-runtime/02-linking-and-loading
- /compilers/08-compilation-technology-applications/01-jit-compilation
- /compilers/08-compilation-technology-applications/02-dsl-design
- /compilers/08-compilation-technology-applications/03-compile-time-metap…
liz's doc public knowledge also offers 3 prompts — things you invoke, where a resource is context you attach.
Read from the server itself, by connecting to it and calling resources/list on 24 September 2026.
A listing does not declare its resources, so asking is the only way to know them, and this
is what the server actually offers rather than what its listing claims. Names only are
stored; connect the server for each resource's type and contents.