# Tempreon MCP MCP Server

> **Tempreon MCP MCP Server** is a hosted, multitenant Model Context Protocol (MCP) server run by **MewCP** (https://mewcp.com), giving AI agents managed access to Tempreon MCP.
>
> MewCP takes care of all MCP infrastructure for you — credential storage, OAuth flows,
> token refresh, and production-grade auto-scaling — so your AI agents can connect to
> third-party services and run freely without you managing any MCP server yourself.
>
> Server page:  https://mewcp.com/mcp/tempreon-mcp
> MewCP docs:   https://docs.mewcp.com
> Full catalog: https://mewcp.com/llms.txt

---

## About

Tempreon provides persistent, personalized AI memory across coding sessions and assistants. Store user preferences, project decisions, technical conventions, and accumulated knowledge; retrieve relevant context at session start, search past decisions, and save new learnings to maintain continuity across AI tools.

---

## Details

- Server ID: `tempreon-mcp`
- Version: v1.139.139
- Tools: 16
- Authentication: OAuth, managed by MewCP
- Transport: http

---

## Access

The gateway URL below serves your **entire MewCP toolset**, not this server on its
own. Pasting a config snippet is not enough — Tempreon MCP has to be in the toolset
first. In order:

1. Add Tempreon MCP to your toolset at https://mewcp.com/mcp/tempreon-mcp
2. Connect your Tempreon MCP account (OAuth); MewCP stores the credential and attaches it to each call
3. Copy your MewCP API key from the dashboard (Developer)
4. Configure your client with the snippet for it below

Once connected, an agent does **not** see this server's tools as top-level tools.
It sees four meta-tools and reaches everything through them:

- `search(query)` — find tools by keyword across the toolset
- `get_schema(tools)` — full description and arguments for the tools you picked
- `list_accounts(provider)` — only when one app has several connected accounts
- `call_tool(server_maskedId, tool_name, args)` — execute

So the list below is what `search` can return for this server, not a set of
callable tool names on their own.

---

## Tools (16)

Descriptions are truncated to 160 characters; call `get_schema`
for the full text and the argument schema. Where a tool is annotated, its type
is shown — treat `destructive` as irreversible.

- `agent` _(write)_ — Inspect your personal AI agents and their runs. Agents are named personas the user defines — a content strategist, an analyst, a researcher — that carry their…
- `create_agent` _(write)_ — Define a new personal AI agent (persona) — a named entity (e.g., a Content Strategist "Riley") with a voice, responsibilities, and authority scopes. Once…
- `dispatch_agent` _(destructive)_ — Dispatch one of your agents to run a task autonomously — a named persona the user has defined (list them with the read-only agent tool, action:"inventory").…
- `get_file` _(read)_ — Retrieve a file from your File Vault by ID, description, or recent uploads. Returns files saved as part of your personal work — surfaced with the context and…
- `log_feedback` _(write)_ — Record feedback on a prior deliverable — approved, edited, rejected, or rated. Closes the learning loop: action + outcome is what Tempreon learns about your…
- `log_work` _(write)_ — Record a significant deliverable you produced — content, analysis, plans, decisions. Creates an action the learning system later pairs with your feedback. Not…
- `manage_task` _(write)_ — Create or update a personal task. Links to your knowledge, context, and identity so tasks carry learning forward. Use for personal work that benefits from…
- `personalize` _(write)_ — Get personalization guidance before drafting for this user. Returns learned preferences, active rules, voice guidance, and non-negotiable hard-stops the user…
- `remember` _(write)_ — Store something Tempreon should know about you — a fact, preference, correction, person, or new project. Every call feeds the learning system that adapts…
- `remove_file` _(destructive)_ — Remove a file from your File Vault. DESTRUCTIVE. Two modes: • Soft-retire (DEFAULT — purge omitted or false): flips the artifact to lifecycle_stage='archived'…
- `save_file` _(write)_ — Save a file to your personal File Vault — tied to your identity, learning, and active contexts. Not generic cloud storage; artifacts link to deliverables,…
- `search` _(read)_ — Search THIS USER'S personal knowledge, past decisions, active projects, and people they know. Returns context-aware results tied to them specifically. Use it…
- `session_end` _(write)_ — Close your session. Captures deliverables, decisions, and observations as a continuity artifact for next time. Run this at the end of a session — without it,…
- `session_start` _(write)_ — Start your Tempreon session. Returns your identity, active projects, learned preferences, and follow-ups from last session. Call this at the start of a…
- `tasks` _(read)_ — List YOUR personal task queue — work tied to your knowledge, projects, and identity: goals, reminders, and work connected to everything else Tempreon knows…
- `show_memory_panel` _(read)_ — Shows what Tempreon is using for you right now: your current focus, your top working rule, your top hard stop, and how to export your data. Apps-capable hosts…

---

## Connect

Gateway URL: https://gateway.mewcp.com/personal/mcp

Every request carries one header:

    Authorization: Bearer <API_KEY>

Replace `API_KEY` with your own key from the dashboard (Developer).

## Apps

### Claude Desktop

Mac & Windows app

- macOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
- Windows: `%APPDATA%\Claude\claude_desktop_config.json`

```json
{
  "mcpServers": {
    "mewcp": {
      "command": "npx",
      "args": [
        "-y",
        "mcp-remote@latest",
        "https://gateway.mewcp.com/personal/mcp",
        "--header",
        "Authorization: Bearer API_KEY"
      ]
    }
  }
}
```

Already have an "mcpServers" section in your config? Just add the server entry inside it.

1. Open Claude Desktop → Settings → Developer → "Edit Config"
2. Paste the snippet inside the outer { } of the config file (merge with your existing "mcpServers" section if you have one)
3. Save the file and restart Claude Desktop
4. Start a new conversation — your tool will be available

### VS Code

Copilot / Cline

- Command Palette → "MCP: Open User Configuration" (opens mcp.json). For one project only, use .vscode/mcp.json instead.

```json
{
  "mcp.servers": {
    "mewcp": {
      "type": "http",
      "url": "https://gateway.mewcp.com/personal/mcp",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}
```

Already have a "servers" section in your mcp.json? Just add the server entry inside it.

1. Open VS Code → Command Palette (Cmd+Shift+P / Ctrl+Shift+P)
2. Run "MCP: Open User Configuration" to open your mcp.json
3. Paste the snippet and save
4. Start the server when prompted (or from the MCP servers view) and use it in Copilot Chat

### Cursor

AI-first editor

- macOS: `~/.cursor/mcp.json`
- Windows: `%USERPROFILE%\.cursor\mcp.json`

```json
{
  "mcpServers": {
    "mewcp": {
      "url": "https://gateway.mewcp.com/personal/mcp",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}
```

Already have an "mcpServers" section in your mcp.json? Just add the server entry inside it.

1. Open Cursor → Settings → Cursor Settings → MCP
2. Click "Add new global MCP server"
3. Paste the snippet and save
4. Restart Cursor

### Codex

OpenAI's CLI agent

- Add the snippet to your Codex MCP config or your standard MCP config file for the CLI tool you use.

```json
{
  "mcpServers": {
    "mewcp": {
      "type": "http",
      "url": "https://gateway.mewcp.com/personal/mcp",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}
```

Codex generally reads a standard MCP server block, so you can add this alongside your other configured servers.

1. Open your Codex MCP config or project-level config file
2. Paste the MewCP server block inside the config JSON/TOML structure your tool expects
3. Save the file and restart Codex
4. Verify the tool is available inside a fresh session

### Claude Code

Anthropic's CLI agent

- ~/.claude.json (user scope) or .mcp.json in your project root — create it if it doesn't exist. Or skip the file and use the CLI command below.

```json
{
  "mcpServers": {
    "mewcp": {
      "type": "http",
      "url": "https://gateway.mewcp.com/personal/mcp",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}
```

Already have an "mcpServers" section in your config? Just add the server entry inside it.

1. Open ~/.claude.json (or .mcp.json in your project root) in a text editor
2. Paste the snippet inside the outer { } (merge with your existing "mcpServers" section if you have one)
3. Save the file and start (or restart) Claude Code
4. Or skip the file entirely and run the CLI command below instead

### OpenCode

Open-source terminal agent

- ~/.config/opencode/opencode.json (global) or opencode.json in your project root — create it if it doesn't exist.

```json
{
  "$schema": "https://opencode.ai/config.json",
  "mcp": {
    "mewcp": {
      "type": "remote",
      "url": "https://gateway.mewcp.com/personal/mcp",
      "enabled": true,
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}
```

Already have an "mcp" section in your opencode.json? Just add the server entry inside it.

1. Open ~/.config/opencode/opencode.json (or opencode.json in your project root) in a text editor
2. Paste the snippet inside the outer { } (merge with your existing "mcp" section if you have one)
3. Save the file and start (or restart) OpenCode

### OpenClaw

Self-hosted agent gateway

- ~/.openclaw/openclaw.json — create it if it doesn't exist.

```json
{
  "mcp": {
    "servers": {
      "mewcp": {
        "transport": "streamable-http",
        "url": "https://gateway.mewcp.com/personal/mcp",
        "enabled": true,
        "headers": {
          "Authorization": "Bearer API_KEY"
        }
      }
    }
  }
}
```

Already have an "mcp" section in your openclaw.json? Just add the server entry inside "servers".

1. Open ~/.openclaw/openclaw.json in a text editor
2. Paste the snippet inside the outer { } (merge with your existing "mcp" section if you have one)
3. Save the file and restart OpenClaw

### Antigravity

Google's agentic IDE

- ~/.gemini/config/mcp_config.json (global) or .agents/mcp_config.json (workspace-local) — create it if it doesn't exist.

```json
{
  "mcpServers": {
    "mewcp": {
      "serverUrl": "https://gateway.mewcp.com/personal/mcp",
      "headers": {
        "Authorization": "Bearer API_KEY"
      }
    }
  }
}
```

Already have an "mcpServers" section in your config? Just add the server entry inside it. Remote servers must use the "serverUrl" field — the legacy "url"/"httpUrl" fields aren't supported.

1. In the editor's agent side panel, click "…" → "MCP Servers" → "Manage MCP Servers" → "View raw config" (Antigravity CLI: type /mcp instead to open the Interactive MCP Manager)
2. Paste the snippet inside the outer { } (merge with your existing "mcpServers" section if you have one)
3. Save the file — the server connects automatically

### Hermes

Nous Research's CLI agent

- config.yaml in your Hermes config directory (~/.hermes) — add this under a top-level "mcp_servers:" key.

```yaml
mcp_servers:
  mewcp:
    url: "https://gateway.mewcp.com/personal/mcp"
    headers:
      Authorization: "Bearer API_KEY"
```

Already have an "mcp_servers" section in your config.yaml? Just add the server entry inside it.

1. Open config.yaml in your Hermes config directory
2. Paste the snippet under the top-level "mcp_servers:" key (merge with existing entries if you have any)
3. Save the file, then run /reload-mcp in Hermes (or start a fresh session)
4. Ask Hermes "Tell me which MCP-backed tools are available right now" to confirm it connected

### DeepSeek Harness

DeepSeek's agent harness

- cordis.yml in your DSH project — or the patch file you mount plugins from.

```yaml
- id: mcp-mewcp
  name: '@deepseek-ai/dsh-mcp-client'
  config:
    serverName: mewcp
    transport: streamable-http
    url: https://gateway.mewcp.com/personal/mcp
    headers:
      Authorization: "Bearer API_KEY"
```

One plugin instance = one MCP server. Add this entry to your plugin list; don't nest it inside another entry.

1. Open cordis.yml (or your patch file) in your DSH project
2. Paste the entry into your plugin list, keeping the leading dash and indentation
3. Restart DSH (or let HMR reload) — tools register as mcp__mewcp__<tool_name>
4. Verify with: dsh web --dump-config | grep -A3 mcp

## SDKs

### Python

fastmcp client

```python
import asyncio
from fastmcp import Client
from fastmcp.client.transports import StreamableHttpTransport

SERVER_URL = "https://gateway.mewcp.com/personal/mcp"
API_KEY = "API_KEY"

transport = StreamableHttpTransport(
    url=SERVER_URL,
    headers={
        "Authorization": f"Bearer {API_KEY}",
    }
)

async def main():
    client = Client(transport)
    async with client:
        tools = await client.list_tools()
        print(tools)

asyncio.run(main())
```

1. Install fastmcp: pip install fastmcp
2. Copy the snippet into your project
3. Replace API_KEY with your key from the dashboard
4. Run your script

### TypeScript

MCP SDK

```typescript
import { Client } from "@modelcontextprotocol/sdk/client/index.js";
import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js";

const SERVER_URL = "https://gateway.mewcp.com/personal/mcp";
const API_KEY = "API_KEY";

const transport = new StreamableHTTPClientTransport(new URL(SERVER_URL), {
  requestInit: {
    headers: {
      Authorization: `Bearer ${API_KEY}`,
    },
  },
});

const client = new Client({ name: "mewcp-client", version: "1.0.0" });
await client.connect(transport);

const tools = await client.listTools();
console.log(tools.tools.map((t) => t.name));
```

1. Install: npm install @modelcontextprotocol/sdk
2. Copy the snippet into your project
3. Replace API_KEY with your key from the dashboard
4. Run with Node 18+ as an ES module (e.g. npx tsx script.ts)