"Understanding Persistent Memory and Context Management" matching MCP servers:

A zero-dependency Node.js playground for debugging how MCP clients authenticate to an MCP server over HTTP.

MCP server for managing devices via JAMF Pro and Microsoft Intune APIs, enabling AI assistants to query and control device management tasks.

Enables role-based order management operations such as viewing orders, checking refund eligibility, issuing refunds, deleting orders, and managing users through MCP tools with audit logging and permission checks.

MCP server that enforces role-based access control for order management, allowing users to view, refund, or delete orders based on their role (USER, MANAGER, ADMIN) with a JWT-authenticated FastAPI frontend.

Deterministic dependency + CVE context for AI coding tools, over the Model Context Protocol. A ~0.85 MB pure-Rust MCP server.

Persistent encrypted memory for AI agents. E2E encrypted private vaults, shared knowledge commons, topic channels, and agent-to-agent DMs. 23 MCP tools, free, no API key needed.

Provides redacted access to a private local knowledgebase for coding agents, allowing them to inspect files while hiding sensitive names and identifiers.

Enables AI assistants to keep and retrieve private context locally, with verifiable receipts and optional Solana anchoring for public proofs.

A local MCP server that acts as a policy-based firewall for personal context, letting users control agent access to their data with deny-by-default rules, per-field grants, and an audit trail.

A security wrapper for MCP servers that provides trust-on-first-use pinning, guardrail scanning, and protection against prompt injection attacks. It acts as an intermediary layer to ensure universal compatibility and secure enforcement of server configurations across various MCP host applications.

Enables role-based order management through MCP tools, allowing users to view and refund orders according to their permissions (USER, MANAGER, ADMIN) with audit logging and JWT authentication handled by a FastAPI client.

Enables authenticated MCP clients to query Security Context tools against a git tag or commit ref while returning only vulnerabilities and fix fingerprints that predate that snapshot, so agents do not receive live bugs at the tag.

A tool for detecting and cleaning Java memory shells via local or SSH remote execution. It enables AI agents to scan Java processes, analyze suspicious class code, and safely remove memory shells after user confirmation.

Guardrails for AI coding agents that enforces rules via compliance receipts, blocking destructive actions and syncing rules across all AI tools.

Enables security analysts to carry structured investigation state across sessions by storing typed observations, hypotheses, tasks, evidence and versioned decisions in a local SQLite graph with full-text search. It also enforces authorized scope and request controls, redacted and content-hashed evidence, duplicate-test signatures and validation gates that leave findings in draft until reproducibly confirmed, then produces technical and executive reports for Antigravity, Codex and other stdio MCP clients.

Enables managing personal information with dynamic topic-based organization (tasks, meetings, contacts, etc.), supporting optional OTP authentication and AES-256 encryption for sensitive data with automatic backups.

MCP server for deterministic context preflight, token counting, and credential redaction for coding agents, with a free local tier up to 12,000 characters and paid HTTP fallback for larger inputs.

Enables MCP-compatible AI agents to save encrypted, DID-signed session checkpoints and resume the latest state across sessions, while keeping secrets and credentials in a local vault.

Enables named, authenticated callers to run read-only introspection of a Google Cloud project and to read and write per-tenant notes that stay isolated between callers. Every request is scope-checked against a reviewed policy, rate-limited per caller, and audited without ever logging argument values.

Local MCP server for private, consent-based speaker identification and attribution, with per-language voiceprints and calibrated match thresholds. It lets AI assistants know who is speaking in a room or transcript without cloud services.