In-depth architectural comparison of the Agentready MCP and Codebase Memory MCP MCP servers. Compare execution transports, security boundaries, tool capabilities, quality scores, and ready-to-paste client installation snippets for Claude, Cursor, Windsurf, and VS Code.
At a Glance & Executive Verdict
Agentready MCP
Knowledge & Memory · Local stdio
Quality: 59/100 (Good) | Auth: No auth required
Codebase Memory MCP
Knowledge & Memory · Local stdio
Quality: 72/100 (Great) | Auth: No auth required
Verdict Summary: Choose Agentready MCP if you need specialized Knowledge & Memory tools running via a local process. Choose Codebase Memory MCP if your workspace requires Knowledge & Memory integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.
Which MCP Server Should You Choose?
Choose Agentready MCP when:
You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
List all websites currently indexed in AgentReady. Use this to check if a domain is already available before submitting it — indexed sites return instant cited answers via ask_site. The index covers developer tools, APIs, cloud platforms, frameworks, databases, and more, and grows as new sites are submitted.
get_site_capabilities
Return the AgentReady capability manifest for a website. If the site is not indexed yet, AgentReady indexes it automatically before returning its freshness, read-only limits, schemas, and available MCP and HTTP endpoints.
plan_site_action
Turn a natural-language request into a grounded, read-only AgentReady plan for a website. If the site is not indexed yet, AgentReady indexes it automatically first. This prototype never executes side effects; it identifies supported steps, sources, risks, and whether a future execution would require confirmation.
submit_site
Index any website so it can be queried with ask_site. Use this when the site is not yet in list_sites. Handles JS-rendered pages (React, Next.js, Vue SPAs) that web_fetch cannot read — uses a four-layer pipeline: llms.txt → HTTP+cheerio → __NEXT_DATA__ extraction → Jina Reader headless browser. Takes ~60 seconds. Once indexed, ask_site queries are instant.
Ready-to-Paste Client Configurations
Paste either (or both) of these JSON server blocks into your client config file (e.g. claude_desktop_config.json or ~/.cursor/mcp.json).
Agentready MCP is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Codebase Memory MCP belongs to Knowledge & Memory using local stdio subprocess. Select Agentready MCP when you need capabilities focused on knowledge & memory and Codebase Memory MCP when you require tools for knowledge & memory.
Query any website's documentation and get cited, multi-page answers in natural language. Use ask_site when you need: (1) answers that synthesize information across multiple pages of a site, (2) documentation from JS-rendered sites (React, Next.js, Vue SPAs) where web_fetch returns empty or partial HTML, (3) citations linking back to the exact source pages, (4) faster results than fetching and reading individual pages one by one. For sites not yet indexed, ask_site auto-crawls and answers in ~60s — no separate submit_site call needed.
refresh_site
Force a full re-crawl of a site to pick up new or changed content. If the site has never been indexed, AgentReady performs the initial indexing automatically. Use when ask_site returns outdated information or when you know the site has recently been updated. Takes ~60 seconds. After completion, ask_site returns fresh content.
rate_answer
Rate the quality of a previous ask_site answer from 1 (not useful) to 5 (excellent). Pass the request_id returned in structuredContent when available so the rating can be tied to the exact answer.
Codebase Memory MCP Tools (14)
index_repository
Index a repository into the graph. Auto-sync keeps it fresh after that.
list_projects
List all indexed projects with node/edge counts.
delete_project
Remove a project and all its graph data.
index_status
Check indexing status of a project.
search_graph
Structural, BM25, and semantic search. Page structural rows with `offset`/`limit` and ranked semantic rows independently with `semantic_offset`/`semantic_limit`.
trace_path
BFS traversal — who calls a function and what it calls (alias: `trace_call_path`). Depth 1-5.
detect_changes
Map git diff to affected symbols + blast radius with risk classification.
query_graph
Execute Cypher-like graph queries (read-only).
get_graph_schema
Node/edge counts, relationship patterns, property definitions per label. Run this first.
get_code_snippet
Read source code for a function by qualified name.
Make any website queryable by AI agents. Index a site then ask questions and get cited answers grounded in its content via RAG. Tools: listsites and asksite. npx -y @agentreadyweb/mcp
Code-intelligence engine that indexes a repo into a persistent knowledge graph — functions, classes, call chains, HTTP routes, cross-service links. 159 languages via tree-sitter + Hybrid LSP, sub-ms structural queries, 99% fewer tokens than grep. Single static binary, zero dependencies, 100% local. npx codebase-memory-mcp