"Buffer" matching MCP servers:

Enables publishing and scheduling posts to Buffer via the createPost GraphQL mutation, extending beyond Buffer's official read-only MCP connector.

Enables publishing and scheduling posts to Facebook, Instagram, YouTube and other channels through Buffer, with Cloudinary media upload and validation plus analytics tools. It provides 23 tools covering channel and post management, media probing and upload, and performance insights for AI-driven content operations.

MCP server for AI agent observability, providing trace and span logging, search, latency/tokens/cost metrics, and anomaly detection using an in-memory buffer.

Provides an external context buffer so a local model can maintain session memory across long tasks and search and page through large documents without loading them whole into its limited context window.

Provides comprehensive geospatial analysis capabilities through Turf.js, enabling spatial measurements, geometric operations, coordinate transformations, and geographic data processing. Supports over 100 geospatial functions including distance calculations, spatial relationships, buffer operations, and grid generation.

Enables any MCP-capable client to search Hong Kong's 1,154 official CSDI spatial datasets in English, Traditional or Simplified Chinese, retrieve them as GeoJSON, and answer questions with counts, sums and charts, interactive 2D/3D maps, feature attribute inspection, or printable static maps without an API key. Optional tools let users geocode, project or buffer geometry, render keyless Esri basemaps, and publish datasets to ArcGIS Online with their own credentials.

Enables easy gRPC requests and Protocol Buffer file information retrieval through natural language commands. Supports unary RPCs with SSL, timeout configuration, and response time statistics.

Enables MCP clients to run whole-dataset GIS operations such as buffer, clip, reproject, overlay, spatial join, dissolve, zonal statistics, and attribute selection by passing file paths in and out, so an entire dataset is processed in a single call instead of feature by feature. It works over Streamable HTTP with a shared filesystem or base64 upload/download tools for remote clients.