No install? Use cloud.anythingmcp.com directly.
Sign in, install the Slab in one click, paste the credentials, mint an MCP API key — done. No Docker, no git clone, no local server to run.
TL;DR
Drive Slab (team wiki) from any AI agent via its GraphQL API: posts, topics, users, search. 6 tools, Bearer auth.
💡 Niente installazione? Vai direttamente su cloud.anythingmcp.com. Accedi, clicca Connectors → Slab, inserisci le credenziali, genera una MCP API key — fatto. Niente Docker, niente
git clone, niente server locale.
Slab + Gemini
Drive Slab (team wiki) from any AI agent via its GraphQL API: posts, topics, users, search. 6 tools, Bearer auth.
Prerequisiti
Le istruzioni di setup complete sono incluse nel connettore stesso (visibili nello store quando lo selezioni). Le variabili d'ambiente richieste sono:
SLAB_API_TOKEN
Step 1 — Ottieni le credenziali
slab.com/v1/graphql).
Setup:
- Sign in to Slab → top-right avatar → Account Settings → Tokens → Create token.
- Pick scopes: at minimum
read posts,read topics,read users. - Set
SLAB_API_TOKEN.
Authentication: Authorization: Bearer ${SLAB_API_TOKEN}.
GraphQL-only: Slab has no REST. The adapter exposes a few curated mutations + queries as wrappers; for arbitrary queries use the auto-injected GraphQL builtins (each GRAPHQL adapter gets slab_graphql_schema, slab_graphql_query, slab_graphql_mutation automatically).
…(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 —Slabdovrebbe 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 |
|---|---|
slab_me | Return the user the token belongs to (id, name, email, organization) |
slab_get_post | Fetch a post by ID with title + content (in markdown) + topics + owner |
slab_search_posts | Search posts by query text |
slab_list_topics | List top-level topics in the organization |
slab_get_topic_posts | List posts within a topic |
slab_create_post | Create a post from markdown content |
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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