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Summary
Manage Buffer (social media scheduling: channels, posts, idea queue, analytics) from any AI agent via GraphQL. 8 tools, Bearer token.
Prova a chiedere
Prompt di esempio per Buffer
Clicca su un prompt per copiarlo. Incollalo in Claude, ChatGPT, Cursor, Gemini, Copilot o OpenClaw per eseguirlo contro questo connettore.
Claude è un'AI e può sbagliare. Verifica sempre le risposte.
💡 Niente installazione? Vai direttamente su cloud.anythingmcp.com. Accedi, clicca Connectors → Buffer, inserisci le credenziali, genera una MCP API key — fatto. Niente Docker, niente
git clone, niente server locale.
Buffer + Gemini
Manage Buffer (social media scheduling: channels, posts, idea queue, analytics) from any AI agent via GraphQL. 8 tools, Bearer token.
Prerequisiti
Le istruzioni di setup complete sono incluse nel connettore stesso (visibili nello store quando lo selezioni). Le variabili d'ambiente richieste sono:
BUFFER_ACCESS_TOKEN
Step 1 — Ottieni le credenziali
This connector wraps the Buffer Publish GraphQL API (graphql.buffer.com).
Setup:
- Sign in at https://publish.buffer.com → top-right avatar → Settings → API access → Generate personal access token.
- Set
BUFFER_ACCESS_TOKEN.
Authentication: Authorization: Bearer ${BUFFER_ACCESS_TOKEN}.
GraphQL-only: Buffer's modern API is GraphQL. The auto-injected buffer_graphql_query / buffer_graphql_mutation / buffer_graphql_schema builtins cover anything not in the typed wrappers below.
Channel = connected social account (Twitter, LinkedIn, Facebook, Instagram, Mastodon, TikTok, Pinterest, YouTube, Bluesky, Threads). Each has an ID; posts must specify channelId(s).
…(continued in the in-app connector instructions)
Step 2 — Installa l'adapter
git clone https://github.com/HelpCode-ai/anythingmcp.git
cd anythingmcp && docker compose up -d
Step 3 — Aggiungi il connettore in Gemini
Gemini CLI legge i server MCP da ~/.gemini/settings.json (o %APPDATA%\gemini\settings.json su Windows). Aggiungi:
{
"mcpServers": {
"anythingmcp": {
"httpUrl": "https://cloud.anythingmcp.com/mcp",
"headers": { "Authorization": "Bearer YOUR_MCP_API_KEY" }
}
}
}
- Ottieni la tua MCP API key da AnythingMCP → Profilo → MCP API Keys → Nuova Key.
- Salva il file e riavvia
gemini. - Esegui
/mcpnella Gemini CLI —Bufferdovrebbe essere elencato come disponibile. - Vertex AI Studio: passa
https://cloud.anythingmcp.com/mcpnell'arraytoolsdella richiesta con lo stesso header Bearer.
Tool disponibili
| Tool | What it does |
|---|---|
buffer_current_user | Return the authenticated user with their orgs |
buffer_list_channels | List connected social channels for an organization |
buffer_list_posts | List posts on a channel with status filter |
buffer_create_post | Schedule or save a draft post on one or more channels |
buffer_update_post | Update a scheduled post's text, schedule, or media |
buffer_delete_post | Delete a post |
buffer_send_now | Send a scheduled post immediately, regardless of due_at |
buffer_list_ideas | List ideas from the org-wide idea queue |
FAQ
Gemini 1.5 Pro o 2.x supportano MCP? Sì — Gemini CLI ≥ 0.4 e la Vertex AI tools API accettano connettori MCP httpUrl con header Bearer.
Prossimi passi
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