Agishub MCP vs Moxie Docs MCP
A side-by-side look at the Agishub MCP and Moxie Docs MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Agishub MCP for knowledge & memory work as a local process; choose Moxie Docs MCP for knowledge & memory. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Agishub MCP when
- You need dedicated capabilities in the Knowledge & Memory domain.
- You prefer a local stdio subprocess transport.
- You want tools like
ai.chat, ai.classify, ai.embed.
Choose Moxie Docs MCP when
- You need dedicated capabilities in the Knowledge & Memory domain.
- Its auth model fits you: OAuth 2.0.
- You want tools like
moxie.get_ai_context, moxie.get_doc_impact, moxie.get_api_context.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Knowledge & Memory | Knowledge & Memory |
| Quality signal | 53/100 · Good | 76/100 · Great |
| Install command | Confirmed | Not confirmed yet |
| Transport | Local subprocess (stdio) | — |
| Auth | Not declared | OAuth 2.0 |
| Pricing | Not declared | Freemium |
| Required env vars | None listed | None listed |
| Verified owner | Community listing | Verified |
| GitHub stars | 0 | 2 |
| Directory activity | 0 views 0 installs 0 upvotes | 44 views 25 installs 4 upvotes |
| Tools | 34 | 12 |
| Full listing | View Agishub MCP | View Moxie Docs MCP |
Tools & capabilities
Agishub MCP tools 34
ai.chatAsk a general-purpose LLM a question or give it an instruction, with an optional system prompt. No external API key required.ai.classifyClassify a text into exactly one of the candidate labels you provide (e.g. sentiment, topic, intent).ai.embedTurn text into a numeric embedding vector for semantic search, RAG and similarity. Multilingual.ai.extractExtract named entities from text — people, organizations, locations, dates and miscellaneous — returned as structured JSON.ai.summarizeSummarize a block of text into a short abstract, with an optional target length. No external API key required.web.browserDrive a headless browser: open a URL and run an ordered list of steps — click, type, press keys, wait, extract text and screenshot. For flows the plain scraper can't reach (logins, forms, multi-step pages).web.crawlCrawl multiple pages of a site, respecting link depth and domain limits. Returns async job_id; results include markdown or HTML per page. Use it to fetch and process many pages of content at once.web.extractFetch any public web page and return its main content as clean, token-efficient Markdown (title, description, headings, links, lists). Set render:true to execute JavaScript first for single-page apps or JS-heavy pages that would otherwise come back empty. Built for RAG and for agents that need to r…web.extract_structuredAI-powered structured extraction: give a URL plus a natural-language prompt and/or a JSON Schema, and get back clean structured JSON (e.g. product name, price, rating). Renders the page in a headless browser first, so it works on SPAs.web.linksReturn every hyperlink on a JavaScript-rendered page as a list of absolute URLs, with options to keep only visible links or only same-site links. Backed by a headless browser. Use it to map a site or seed a crawler.web.mapDiscover all URLs reachable from a domain within a link depth limit. Returns a flat list of absolute URLs, respects robots.txt crawl delays. Use it to map a site's structure before crawling.web.scrapeExtract specific elements from a JavaScript-rendered page by CSS selector. Give a list of selectors (e.g. 'h1', '.price', 'a.product') and get back the text and attributes of every match. Backed by a headless browser, so it works on SPAs and JS-heavy pages.- +22 more on the listing page
Moxie Docs MCP tools 12
moxie.get_ai_contextCompact pre-edit briefing: repo status, verified commands, top conventions, open gaps, team notes. Read this first.moxie.get_doc_impactGiven the paths you're about to change (and any you're deleting), returns the conventions, gaps, and existing docs whose evidence overlaps them - and flags net-new/undocumented surfaces.moxie.get_api_contextGiven paths you're about to touch, returns structured context for any API endpoints they map to: method, path, schema, and known consumers/features.moxie.review_changeSelf-review a change before opening the PR; returns a severity-ranked verdict (clean / warnings / must-fix) covering convention breaches, stale docs, undocumented surface, and broken references.moxie.get_conventionsDiscovered coding conventions, grouped by category, with confidence scores, agent guidance, and source-file citations.moxie.search_docsSemantic + keyword search over generated docs, conventions, gaps, and AI context.moxie.get_doc_gapsUnresolved documentation gaps with severity and the paths they concern.moxie.get_documentation_opportunitiesRecommended doc work: missing docs, drift repairs, and PR templates.moxie.get_documentation_patternsHow the repository organizes and maintains its docs (where new docs belong).moxie.list_docsPaginated, section-grouped table of contents of every generated doc.moxie.propose_doc_updateAdd or update a doc as part of your current change; returns the target path + Markdown to write into your branch.moxie.propose_doc_removalRemove a Moxie Docs-tracked doc your change makes obsolete; returns the path to delete in your branch.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Agishub MCP
{
"mcpServers": {
"agent-memory": {
"command": "npx",
"args": [
"-y",
"@agishub/mcp"
]
}
}
}
Moxie Docs MCP
No confirmed install command for Moxie Docs MCP yet — follow the setup steps linked from its listing page rather than a guessed package name.
Frequently asked questions
Agishub MCP is categorized under Knowledge & Memory and uses a local stdio subprocess. Moxie Docs MCP belongs to Knowledge & Memory and uses an install path we have not confirmed yet. Pick Agishub MCP for knowledge & memory work and Moxie Docs MCP for knowledge & memory.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client. Moxie Docs MCP has no confirmed install command yet — follow its own setup instructions.
Agishub MCP has no declared pricing — check the project's own site. Moxie Docs MCP is listed as freemium — a free tier with paid plans. Auth: oauth 2.0. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add agent-memory and moxie-docs-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Agishub MCP has a quality signal of 53/100 (Good) with 0 views, 0 installs and 0 GitHub stars. Moxie Docs MCP has 76/100 (Great) with 44 views, 25 installs and 2 GitHub stars.