"Malt" matching MCP servers:

Self-hosted governance layer between an AI assistant and your data: allow/deny policy, deterministic PII masking, row caps, and a hash-chained audit log with an Ed25519-signed receipt for every access, verifiable offline.

Enables AI assistants to identify and quantify value leaks in organizations using Melt's methodology, providing structured estimates instead of generic vendor lists.

Policy-gated agent spend with signed receipts and rail-extract audit: a fail-closed gate issues a COSE receipt for every allowed payment, and the audit reconciles those receipts against a rail extract so a settlement with no receipt is named rather than assumed. It settles on a mock rail, holding no wallet and signing no transaction.

MCP server for MyAnimeList that enables searching anime/manga, getting details, rankings, seasons, characters, reviews, and user profiles without authentication, and managing personal anime/manga lists with authentication (token required).

Enables AI agents to store and retrieve provenance-aware facts with source, age, and boundaries, supporting search, read, propose, and local telemetry via MCP tools.

Bridges Cursor and Claude Desktop with the OpenClaw and Moltbook ecosystems to manage personal AI agents and communication gateways across platforms like WhatsApp and Discord. It provides MCP tools to invoke agents, manage sessions, and handle social agent interactions within a secure, virtualized environment.

GiveRadar's MCP server gives AI agents verified data on 7 million+ nonprofits across 65+ countries, sourced from official government registries. Tools let agents search charities, verify a charity by registration number or EIN, compare integrity scores, and find similar organizations.

Enables agents to search MCP servers ranked by measured handshake checks, tool lists, repository signals, and signed reports, with open data.

Local MCP server for Java heap dump analysis with Eclipse MAT: heap overview, histograms, dominator trees, threads, OQL, leak suspects, and OOM diagnosis.

Liminal turns objectives into structured work by strategizing through an atomic, deterministic basis: setting guardrails around scope, compiling resources and constraints, uncovering gaps, and organizing research and next steps. All while carrying continuity and priorities forward so your AI builds on what’s already done.

Enables interaction with the SuperOps.ai PSA/RMM platform for managing clients, tickets, assets, and technicians via GraphQL API.