إعداد عملاء الذكاء الاصطناعي
إعدادات جاهزة للنسخ لكل عميل، مولّدة من البيانات نفسها التي تعرضها صفحة Connect AI في لوحة التحكم (packages/studio/client/src/connect-clients.ts). استبدل /path/to/ReelForge بمجلد ReelForge لديك (على Windows اكتبه بالشكل C:/Users/you/ReelForge). وتملأ صفحة Connect AI (/connect) المسارات الحقيقية والـ toolsets التي تختارها والـ token عند الحاجة.
- stdio: يشغّل العميل
reelforge mcpبنفسه، ولا حاجة إلى تشغيل أي شيء آخر. - HTTP: أبقِ
reelforge studioيعمل؛ يتصل العميل بالعنوانhttp://127.0.0.1:4310/mcp. إذا رُبطت لوحة التحكم بعنوان آخر، أضف الترويسةAuthorization: Bearer <token>(راجع الأمان).
ملاحظة: هذه الصفحة مولّدة من الكود. العناوين والشرح بالعربية، أما الأوصاف داخل الجداول فتُقرأ من الكود وتبقى بالإنجليزية.
| العميل | stdio | HTTP |
|---|---|---|
| Claude Code | ✓ | ✓ |
| Claude Desktop | ✓ | |
| Cursor | ✓ | ✓ |
| VS Code · Copilot | ✓ | ✓ |
| Windsurf | ✓ | ✓ |
| Gemini CLI | ✓ | ✓ |
| Codex CLI | ✓ | ✓ |
| Zed | ✓ | ✓ |
| Continue | ✓ | ✓ |
| LM Studio | ✓ | ✓ |
| OpenAI-compatible | ✓ |
Claude Code
توثيق العميل: https://docs.anthropic.com/en/docs/claude-code/mcp
stdio
المكان: Terminal (or .mcp.json in the project, already included in this repository)
claude mcp add reelforge -- node /path/to/ReelForge/packages/cli/bin/reelforge.js mcp --root /path/to/ReelForgeTools appear as mcpreelforge<tool>. Check with claude mcp list.
HTTP
المكان: Terminal
claude mcp add --transport http reelforge http://127.0.0.1:4310/mcpKeep reelforge studio running while you use it.
Claude Desktop
توثيق العميل: https://modelcontextprotocol.io/quickstart/user
stdio
المكان: Settings → Developer → Edit Config (claude_desktop_config.json)
{
"mcpServers": {
"reelforge": {
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
}
}
}Restart Claude Desktop after saving.
Claude Desktop connects to remote servers only through HTTPS connectors; use stdio locally.
Cursor
توثيق العميل: https://docs.cursor.com/context/model-context-protocol
stdio
المكان: .cursor/mcp.json in the project (or ~/.cursor/mcp.json for every project)
{
"mcpServers": {
"reelforge": {
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
}
}
}HTTP
المكان: .cursor/mcp.json or ~/.cursor/mcp.json
{
"mcpServers": {
"reelforge": {
"url": "http://127.0.0.1:4310/mcp"
}
}
}VS Code · Copilot
توثيق العميل: https://code.visualstudio.com/docs/copilot/chat/mcp-servers
stdio
المكان: .vscode/mcp.json in the project
{
"servers": {
"reelforge": {
"type": "stdio",
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
}
}
}Use Copilot Chat in Agent mode and enable the reelforge tools.
HTTP
المكان: .vscode/mcp.json in the project
{
"servers": {
"reelforge": {
"type": "http",
"url": "http://127.0.0.1:4310/mcp"
}
}
}Windsurf
توثيق العميل: https://docs.windsurf.com/windsurf/cascade/mcp
stdio
المكان: Settings → Cascade → MCP servers → View raw config (~/.codeium/windsurf/mcp_config.json)
{
"mcpServers": {
"reelforge": {
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
}
}
}HTTP
المكان: ~/.codeium/windsurf/mcp_config.json
{
"mcpServers": {
"reelforge": {
"serverUrl": "http://127.0.0.1:4310/mcp"
}
}
}Gemini CLI
توثيق العميل: https://github.com/google-gemini/gemini-cli/blob/main/docs/tools/mcp-server.md
stdio
المكان: .gemini/settings.json in the project (or ~/.gemini/settings.json)
{
"mcpServers": {
"reelforge": {
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"],
"timeout": 600000
}
}
}Check it with /mcp inside Gemini CLI.
HTTP
المكان: .gemini/settings.json or ~/.gemini/settings.json
{
"mcpServers": {
"reelforge": {
"httpUrl": "http://127.0.0.1:4310/mcp",
"timeout": 600000
}
}
}Codex CLI
توثيق العميل: https://github.com/openai/codex/blob/main/docs/config.md
stdio
المكان: ~/.codex/config.toml
[mcp_servers.reelforge]
command = "node"
args = ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
startup_timeout_sec = 30
tool_timeout_sec = 600HTTP
المكان: ~/.codex/config.toml
[mcp_servers.reelforge]
url = "http://127.0.0.1:4310/mcp"Streamable HTTP needs a recent Codex release. With a token, export REELFORGE_TOKEN before starting Codex.
Zed
توثيق العميل: https://zed.dev/docs/ai/mcp
stdio
المكان: Zed settings.json
{
"context_servers": {
"reelforge": {
"source": "custom",
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
}
}
}HTTP
المكان: Zed settings.json
{
"context_servers": {
"reelforge": {
"source": "custom",
"url": "http://127.0.0.1:4310/mcp"
}
}
}Continue
توثيق العميل: https://docs.continue.dev/customize/deep-dives/mcp
stdio
المكان: .continue/mcpServers/reelforge.yaml in the project
name: ReelForge
version: 1.0.0
schema: v1
mcpServers:
- name: reelforge
command: 'node'
args:
- '/path/to/ReelForge/packages/cli/bin/reelforge.js'
- 'mcp'
- '--root'
- '/path/to/ReelForge'MCP tools are available in Agent mode.
HTTP
المكان: .continue/mcpServers/reelforge.yaml in the project
name: ReelForge
version: 1.0.0
schema: v1
mcpServers:
- name: reelforge
type: streamable-http
url: 'http://127.0.0.1:4310/mcp'LM Studio
توثيق العميل: https://lmstudio.ai/docs/app/plugins/mcp
stdio
المكان: Program → Install → Edit mcp.json
{
"mcpServers": {
"reelforge": {
"command": "node",
"args": ["/path/to/ReelForge/packages/cli/bin/reelforge.js", "mcp", "--root", "/path/to/ReelForge"]
}
}
}Pick a model with tool use; a vision model can also read preview_frames images.
HTTP
المكان: Program → Install → Edit mcp.json
{
"mcpServers": {
"reelforge": {
"url": "http://127.0.0.1:4310/mcp"
}
}
}OpenAI-compatible
توثيق العميل: https://spec.openapis.org/oas/v3.1.0
HTTP
المكان: Any agent framework with function calling (or a GPT Action importing the OpenAPI URL)
import json, requests
API = "http://127.0.0.1:4310/api/v1"
HEADERS = {}
# Every ReelForge tool as an OpenAI function definition
tools = requests.get(f"{API}/tools?format=openai", headers=HEADERS).json()
def call_tool(name: str, arguments: str) -> str:
r = requests.post(f"{API}/tools/{name}", json=json.loads(arguments or "{}"), headers=HEADERS)
data = r.json() # {"ok": bool, "result": {...}, "text": "...", "error": "..."}
return data["text"] if data.get("ok") else "Error: " + data.get("error", "")
# OpenAPI 3.1 (one operation per tool): http://127.0.0.1:4310/api/v1/openapi.jsonPass tools to chat.completions.create(…, tools=tools) and answer each tool call with call_tool().
No MCP: uses the REST API (/api/v1) that serves the same tools.