"author:KaryawanSurga" matching MCP servers:

Enables AI agents and developers to introspect SQLite schemas, run sandboxed read-only queries with pagination, inspect query plans, and generate token-dense database summaries for LLM context. All operations enforce multi-layer read-only safety so databases can be explored without risk of mutation.

Enables coding agents to get a compact, token-budgeted map of any repository in one call, including file tree, language stats, entry points, and key symbols, so they read only what they need.

Lets agents and CLI users inspect the shape of large JSON and JSONL files and extract exactly the values they need using jq-like expressions, returning compact bounded results instead of flooding context.

Enables auditing MCP servers' tools by their estimated context token cost, ranking verbose names, descriptions, and schemas before they consume the agent window. Can run as an MCP tool so agents can budget their own context.

Aggregates many MCP servers behind one local endpoint with namespaced tools, profiles, policy, budgets, audit logs, and a dashboard over stdio or HTTP.

Aggregates multiple MCP servers behind a single endpoint so that clients can reach every one of their tools through one connection instead of configuring each server separately. It simplifies setup and keeps tool access in one place when many servers are in play.

Enables users to turn any OpenAPI 3.x spec into callable MCP tools at runtime, letting agents inspect and invoke API operations directly from JSON or YAML specifications without code generation or build steps.