"SQLite" matching MCP servers:

Record Python/Rust/TypeScript program runs to local SQLite; query call trees, exceptions, and value flow over MCP — refuses rather than guesses. Not the unrelated Telegram sensorium-mcp.

Local-first dashboard + MCP server that parses Claude Code and Codex JSONL files into a SQLite cost / token tracker. Per-MCP and per-tool breakdown, session drill-down, dedup by request_id; never talks to vendor APIs

Transparent Go proxy that intercepts, signs, rate-limits, redacts, and audits all MCP JSON-RPC tool calls without modifying client or server. Stores to JSONL or SQLite with HMAC-SHA256 signatures.

Enables local-first observability for MCP agent workflows by recording tool calls, prompts, latency, and token usage in a local SQLite database, and provides tools for inspecting, comparing, exporting, and generating dashboards from traces.

A production-ready TypeScript template for building MCP servers with dual transport support (stdio/HTTP), OAuth 2.1 foundations, SQLite caching, observability, and security features including PII sanitization and rate limiting.

Transparent MCP proxy with OpenTelemetry tracing. Wrap any MCP server, persist traces to SQLite · Postgres · MySQL. No code changes needed.

Enables AI agents to query MQTT message history stored in SQLite, including topic inventories, last values, historical data, silent devices, and collector connection gaps. Supports publishing messages when write mode is enabled.

Enables explaining Linux incidents over SSH with baseline-aware MCP tooling, including live diagnostics, SQLite history, and review-first workflows.

MCP-native health monitoring that probes MCP servers using the list_tools protocol handshake, detects version drift, stores history in SQLite, and generates an HTML dashboard.

A flight recorder for Claude Code that captures tool calls and observations into a SQLite database, then classifies them into a distilled timeline for incident troubleshooting.

Enables MCP clients to call a hello tool and access observability features, including metrics and request traces, through a Streamable HTTP transport with SQLite-backed storage.

Enables querying UniFi UDM IPS/IDS threat events and security logs stored in SQLite via MCP tools, allowing an LLM to analyze network security data with filtering and aggregation.

Monitors MCP protocol traffic across legacy and modern lanes, records usage evidence in a durable SQLite ledger, and recommends when the legacy fallback can safely be removed.

Enables natural-language querying and investigation of homelab logs from syslog, Docker, OTLP, and AI transcripts, with SQLite full-text search, timeline correlation, incident clustering, and fleet topology insights.

A Python utility for adding usage tracking, analytics, and audit trails to MCP servers using SQLite-backed persistence. It enables developers to monitor tool, prompt, and resource activity and expose these statistics directly to LLM clients.

Provides financial audit reporting and ledger query tools for AI agents, enabling generation of compliance, risk, and transaction reports and querying of transaction data, balances, and summaries from an in-memory SQLite database via MCP.

Enables LLMs to query real job data and summarize backend job failures using MCP tools backed by a SQLite database.

Enables AI agents to self-report every tool call, token usage, decision, and session grade into a local SQLite store, so users can trace execution, audit reasoning, and see per-session costs in a local dashboard. Also supports proxy mode to intercept and trace MCP tool invocations for agents that cannot self-report.

Enables LLM agents to discover and invoke guarded web search, read-only SQLite queries, and sandboxed file read/write tools over the Model Context Protocol. It adds schema validation, rate limiting, output sanitization, request-ID logging, and Prometheus metrics at the protocol boundary.

A local gateway that caches LLM prompts and tool results, stores searchable compressed context, and relays downstream MCP tools under deny-by-default rules. It keeps everything in one SQLite database with a single ledger tracking tokens paid upstream versus tokens avoided, plus a web console for live metrics.