What is the key difference between Kage and Context7?

Kage belongs to the Knowledge & Memory category with local stdio execution, while Context7 belongs to the Knowledge & Memory category with local stdio execution.

How do I install Kage or Context7 in Claude Desktop or Cursor?

Copy the mcpServers JSON configuration snippet provided on this page into your claude_desktop_config.json or ~/.cursor/mcp.json file and restart your AI client.

Are Kage and Context7 free or paid?

Kage operates under a Free / Open Source model (No auth required). Context7 operates under a Freemium model (API Key required).

Which MCP server has more tools and community activity?

Kage lists 6 tools with 0 views and 32 GitHub stars. Context7 lists 5 tools with 3 views and 60,433 GitHub stars.

Can I use both Kage and Context7 together in the same MCP host?

Yes! MCP hosts like Claude Desktop, Cursor, Windsurf, Cline, and VS Code support configuring multiple servers under the mcpServers object simultaneously.

How do I install Kage or Context7 in Claude Desktop, Cursor, or Windsurf?

Both servers follow the standard Model Context Protocol configuration format. Simply copy the JSON block from the configuration section above and paste it into your AI client's mcpServers configuration object (for instance in claude_desktop_config.json or ~/.cursor/mcp.json ), then completely restart or refresh the application.

Are Kage and Context7 free to use, or do they require API keys?

Kage is listed under a Free / Open Source model with No auth required . Context7 operates under a Freemium model with API Key required . If environment variables are required (such as API keys), be sure to define them under the env key in your MCP client's configuration file.

Can I run both Kage and Context7 at the same time in my AI client?

Yes! MCP clients support multi-server orchestration. You can include both kage-core-kage and upstash-context7 as distinct keys inside the single mcpServers object in your configuration file. Your AI assistant will automatically select and call the appropriate tool from either server during chat sessions.

Which MCP server has higher directory engagement and quality ratings?

On AllMCPs, Kage has a Quality Score of 55 /100 ( Good ) with 0 views, 0 installs, and 32 GitHub stars. Context7 holds a Quality Score of 45 /100 ( Fair ) with 3 views, 0 installs, and 60,433 GitHub stars.

Side-by-Side Model Context Protocol Comparison

Kage vs Context7

In-depth architectural comparison of the Kage and Context7 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

Kage

Knowledge & Memory · Local stdio

Quality: 55/100 (Good) | Auth: No auth required

Context7

Knowledge & Memory · Local stdio

Quality: 45/100 (Fair) | Auth: API Key required

Verdict Summary: Choose Kage if you need specialized Knowledge & Memory tools running via a local process. Choose Context7 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 Kage 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).
Primary tools included: Memory stored as plain JSON in git following Open Knowledge Format, Deterministic verification rejecting stale or hallucinated citations, Local-only operation with no account or API key required.

Explore Kage Details

Choose Context7 when:

You need dedicated capabilities in the Knowledge & Memory domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: API Key required (Freemium).
You have access to required keys: CONTEXT7_API_KEY.
Primary tools included: Version-specific documentation retrieval, Supports CLI commands and MCP server integration, Library ID resolution for precise doc fetching.

Explore Context7 Details

Feature & Specification Comparison

Specification	Kage kage-core Knowledge & Memory	Context7 upstash Knowledge & Memory
Summary	Verified, git-native memory for coding agents. Memory is plain JSON packets committed in your repo, each checked against the code it cites — hallucinated citations rejected at write, stale or changed memory withheld at recall, plus diff-time stale-catch. Local-only (BM25 + vectors), no account, no API key. npx -y @kage-core/kage-graph-mcp install	Up-to-date code documentation for LLMs and AI code editors.
Category & Scope	Knowledge & Memory	Knowledge & Memory
Quality signal	55/100 (Good)	45/100 (Fair)
Transport Protocol	Local Subprocess (stdio)	Local Subprocess (stdio)
Auth Requirement	No auth required	API Key required
Pricing Model	Free / Open Source	Freemium
Required Env Vars	None required	`CONTEXT7_API_KEY`
Compatible Clients	Claude DesktopCursorWindsurfClineVS Code	Claude DesktopCursorWindsurfClineVS Code
Install path signal	`npx · high`	`npx · low`
Engagement & Health	0 views 0 copies 0 upvotes 32 stars	3 views 0 copies 0 upvotes 60,433 stars
Verified / Official	Community Listing	Community Listing
Open full listing	View Kage Listing	View Context7 Listing

Tools & Capabilities Breakdown

Kage Tools (6)

Memory stored as plain JSON in git following Open Knowledge Format

Deterministic verification rejecting stale or hallucinated citations

Local-only operation with no account or API key required

Background proxy for zero-wiring integration with Anthropic agents

Per-directory auto-attach configuration for seamless agent routing

Compatibility with multiple coding agents including Claude Code and Codex

Context7 Tools (5)

Version-specific documentation retrieval

Supports CLI commands and MCP server integration

Library ID resolution for precise doc fetching

OAuth authentication with optional API key for rate limits

Multi-language documentation support

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).

Kage Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "kage-core-kage": {
      "command": "npx",
      "args": [
        "-y",
        "@kage-core/kage-graph-mcp"
      ]
    }
  }
}

Context7 Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "upstash-context7": {
      "command": "npx",
      "args": [
        "-y",
        "upstash-context7"
      ],
      "env": {
        "CONTEXT7_API_KEY": "YOUR_CONTEXT7_API_KEY_HERE"
      }
    }
  }
}

Frequently Asked Questions

Kage is categorized under Knowledge & Memory and uses a local stdio subprocess. In contrast, Context7 belongs to Knowledge & Memory using local stdio subprocess. Select Kage when you need capabilities focused on knowledge & memory and Context7 when you require tools for knowledge & memory.

More alternatives to Kage More alternatives to Context7 Knowledge & Memory category hub