What is the key difference between Keymem and Tempguru MCP?

Keymem belongs to the Workplace & Productivity category with local stdio execution, while Tempguru MCP belongs to the Workplace & Productivity category with local stdio execution.

How do I install Keymem or Tempguru MCP 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 Keymem and Tempguru MCP free or paid?

Keymem operates under a Free / Open Source model (No auth required). Tempguru MCP operates under a Free / Open Source model (No auth required).

Which MCP server has more tools and community activity?

Keymem lists 12 tools with 2 views and 3 GitHub stars. Tempguru MCP lists 12 tools with 3 views and 2 GitHub stars.

Can I use both Keymem and Tempguru MCP 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.

Side-by-Side Model Context Protocol Comparison

Keymem vs Tempguru MCP

In-depth architectural comparison of the Keymem and Tempguru 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

Keymem

Workplace & Productivity · Local stdio

Quality: 64/100 (Good) | Auth: No auth required

Tempguru MCP

Workplace & Productivity · Local stdio

Quality: 64/100 (Good) | Auth: No auth required

Verdict Summary: Choose Keymem if you need specialized Workplace & Productivity tools running via a local process. Choose Tempguru MCP if your workspace requires Workplace & Productivity integration with local subprocess execution. Both servers can be configured concurrently in your client's mcpServers manifest.

Which MCP Server Should You Choose?

Choose Keymem when:

You need dedicated capabilities in the Workplace & Productivity domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: recall, browse_keys, read_key.

Explore Keymem Details

Choose Tempguru MCP when:

You need dedicated capabilities in the Workplace & Productivity domain.
You prefer local stdio subprocess transport architecture.
Your security boundary fits: No auth required (Free / Open Source).
Primary tools included: plan_staffing, save_staffing_plan, get_plan.

Explore Tempguru MCP Details

Feature & Specification Comparison

Specification	Keymem donggyun112 Workplace & Productivity	Tempguru MCP tempguru-co Workplace & Productivity
Summary	Associative key-graph memory for LLM agents — recall by association, not vector similarity.	MCP server for W-2 event staffing across 345 US/CA markets: plan_staffing planner, live rates, availability, compliance, the Event Staffing Rate Index, and quote requests. npx -y tempguru-mcp
Category & Scope	Workplace & Productivity

Tools & Capabilities Breakdown

Keymem Tools (12)

recall

Search long-term memory for what is already known about the user, project, or topic — call this before your first reply and whenever the topic shifts. Always pass the active namespace when known. Returns matching key clusters only (not memory content): canonical concept, aliases, key type, match score, linked-memory count, hub status, and specificity. For a core lookup, complete read_key(key_id, original_query, namespace) then read_memory(memory_id, via_key_id, namespace): only the full read grows depth/access, reinforces the traversed edge, and learns aliases. Use short focused noun queries and decompose multi-fact questions into several recall calls. inject:true is only an unconfirmed passive preview and must not replace that traversal; injected memories are not reinforced. inject_top_k defaults to 1; inject_max_chars defaults to 2000 and marks truncated previews. An empty result returns {status:'no_match', nearest_keys} — the closest stored concepts below the gate; retry with one of those concepts when relevant.

browse_keys

Browse the vocabulary of one namespace when recall has no hit or you need an entry point. Returns active key clusters with hubs first, then by linked-memory count. This is index metadata only; continue with read_key(key_id, query, namespace) and read_memory(memory_id, via_key_id, namespace).

read_key

List the memories stored under one key (concept), ranked. Returns the canonical key, its aliases, and hub metadata plus ranked memory IDs and metadata — never memory content. Always pass the original focused query and active namespace when known: handles are then ranked by content relevance, which is essential for hubs. Call read_memory(memory_id, via_key_id=key_id, namespace) on the selected handle to confirm the fact and reinforce the path. Use limit/offset to page without flooding context.

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).

Keymem Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "donggyun112-keymem": {
      "command": "npx",
      "args": [
        "-y",
        "keymem"
      ]
    }
  }
}

Tempguru MCP Configuration

mcpServers (Claude Desktop / Cursor)

{
  "mcpServers": {
    "tempguru-co-tempguru-mcp": {
      "command": "npx",
      "args": [
        "-y",
        "tempguru-mcp"
      ]
    }
  }
}

Frequently Asked Questions

Keymem is categorized under Workplace & Productivity and uses a local stdio subprocess. In contrast, Tempguru MCP belongs to Workplace & Productivity using local stdio subprocess. Select Keymem when you need capabilities focused on workplace & productivity and Tempguru MCP when you require tools for workplace & productivity.