"Setting up SQL Server connections for agent querying" matching MCP servers:

C# SQL Agent MCP server featuring raw SQL input, strict AST validation, and an embedded Admin UI. Eliminates LLM hallucinations and security risks across 6 major databases.

A personal work twin for any AI agent. It briefs agents on the guidance you have confirmed, checks consequential actions against explicit, expiring grants and asks otherwise, and turns your corrections into lessons only you can confirm.

Enables AI assistants to safely explore and query MySQL, MariaDB, PostgreSQL, SQLite and StarRocks databases through read-only tools for schema listing, table description, schema search, row sampling, query execution, and plan explanation. Enforces least-privilege accounts, engine-level read-only sessions with timeouts, parsed SQL guardrails, and column masking so runaway or unsafe queries are refused.

Gives AI coding tools reviewed access to PostgreSQL, MySQL, SQL Server, and SQLite databases, letting read-only queries run instantly while every data or schema change pauses for human approval in a review dialog. It also exposes schema introspection for agents and a way to open the connection manager.

Two-way Burp Suite MCP bridge enabling AI agents to capture traffic, analyze endpoints, queue scans, and send findings back to Burp.

An MCP server that lets Claude query a mock business SQL database in plain language through read-only tools, with server-side guardrails that enforce SELECT-only queries and block access to sensitive payment data.

A governed SQL gateway for untrusted AI agents, providing controlled access to PostgreSQL, MySQL, and OceanBase with RBAC, field ACLs, row policies, and cost controls.

Enables agents to run SELECT-only queries and inspect table metadata against configured databases via MCP Proxy, with timeouts, row and byte caps, and audit logging.

Enables assistants to inspect schemas and run bounded, read-only SQL queries over synthetic retail data with database-enforced guardrails, resource limits, and blocked write attempts.

Enables LLMs to propose UPDATE/DELETE SQL that is run in a transaction, measured, and rolled back, requiring human approval before applying to prevent unauthorized changes.

Validates SQL queries via AST parsing, ensuring they are single read-only SELECTs on allowed tables with enforced LIMITs, and masks PII columns based on user roles. Provides a tamper-evident audit log and runs fully offline.

Enables AI agents to explore and query a SQL database safely, answering questions with real data while blocking writes, hiding protected columns, restricting results to one tenant's rows, and logging every call to an audit trail.

Enables AI agents to safely query and explore SQLite databases through read-only, guard-protected tools that block writes, sensitive table access, and runaway queries.

Enables read-only querying and diagnostics for dual SQL Server 2019 instances with rate limiting and security controls, accessible via MCP tools over HTTP.

Enables AI agents to safely query SQL databases through read-only tools for describing entities, reading records, and aggregating records, with view-based access and fail-closed per-user row-level security.

Enables secure database operations on SQL Server instances through a three-tier safety system, supporting schema exploration, query execution, performance analysis, and data export with configurable security levels from read-only to full development access.

Enables AI agents to query Postgres databases read-only over the Model Context Protocol through three narrow tools, validating every statement as a single SELECT with an enforced row limit before it reaches the database. Guards against destructive statements, banned functions, system catalogs, and runaway queries via AST parsing plus a SELECT-only Postgres role.

Enables AI assistants to explore and analyse local CSV, Parquet or JSON files through validated read-only SELECT queries, with schema discovery, profiling and query-plan tools. Results are capped, timed, PII-masked and audit-logged inside a locked DuckDB sandbox that cannot write, reach the network or read other files.

Screens AI agent tool calls before execution and tool results before the agent reads them, acting as an MCP proxy and hooks adapter with shadow, enforce, and strict policy modes.

Provides tools to issue, verify, and export cryptographically signed receipts for AI agent actions, enabling tamper-proof audit trails for compliance with regulations like the EU AI Act.

Registers a set of inert, tempting decoy tools with any MCP-capable client so that any call from a hijacked or prompt-injected agent instantly raises an alert with full attack context and a per-call trace token. Also plants worthless canary tokens in honeypot files that trigger zero-false-positive leak alerts when they surface in agent output, files, or outbound requests.

Local static inspection of MCP and AI-agent tool manifests before attachment, reporting findings and missing evidence without executing proposed tools. Results do not establish runtime safety.

Cryptographic accountability for AI agents. Ed25519-signed receipts for every MCP tool call. Constraints, chains, AI judgment, invoicing, and local dashboard included.

Security scanning, prompt injection detection, secret leak detection, and agent permission auditing for AI agent workflows.

Provides AI assistants with specialized tools to interact with NIST's Open Security Controls Assessment Language (OSCAL) framework. It enables agents to retrieve schemas, explore models, and generate valid OSCAL documentation for security compliance automation.

agent-bom is an open security scanner and self-hosted control plane for AI, MCP, and cloud infrastructure. The default scan profile in MCP server mode exposes 8 MCP tools. Additional profiles provide inventory, findings, compliance, graph, and runtime workflows. See the published Glama release for its packaged version.

Enables AI agents to securely store and retrieve secrets and make authenticated API calls on their behalf, keeping API keys out of conversation context and supporting local file or GCP Secret Manager backends.

MCP server for AI agent guardrails — validates and signs agent decisions (OAA tokens) so third parties can verify them without server access

A neutral authority layer for agent runtimes, providing sovereign verification and vault-governed custody tools via MCP.

Enables coding agents to send files and notes into approved Zas channels and read items back, with content encrypted before leaving the machine and scoped, revocable agent access.