"Code Execution" matching MCP servers:

Enables agents to interact with the Logflare API by writing JavaScript functions that run in a Vercel Sandbox, using three tools: search, execute_read, and execute_write.

MCP server that provides read-only analysis of Claude Code session transcripts, enabling queries about project activity, session details, and tool usage.

A Model Context Protocol server for Zoho Site24x7 that uses a JavaScript sandbox to execute API calls, enabling management of monitors, accounts, and MSP/BU tenancy through natural language.

Maintenance, recovery, and observability for Claude Code. CLI + MCP server + dashboard.

Enables bounded, deterministic triage verdicts for server health, fleet status, and timeline investigation through a simulated execution-boundary MCP server.

Enables AI agents to trace Python code execution in real time via PEP 669, exposing call trees, variable deltas, and async context through MCP tools.

Enables time-travel debugging for AI agent sandboxes using Firecracker microVMs, with tools for code execution, file operations, and VM snapshot/restore via MCP.

Surface Claude Code token usage, estimated cost, and plan-limit status in any MCP client. Enables agents to query usage data from local logs and Anthropic API.

Claude Code token usage and cost visibility for MCP-capable agents.

Echo tool MCP server that extracts and logs W3C Trace Context from requests to verify propagation from Claude Code.

Enables MCP clients to query and triage security findings published to BigQuery and correlate them with execution, sandbox, and diagnostic traces in Cloud Logging. Exposes tools, resources, and prompts for filtering issues by severity, status, repository, or CWE, retrieving patch diffs and verification results, and diagnosing why a remediation or verification run failed.

An MCP server that records agent execution metrics and exposes a Context Window Explorer to visualize exactly what entered the model's context window across sessions, tokens, and tool calls.

Read-only MCP server for Grafana Loki: lets AI agents (Claude Code, Cursor, Copilot) discover labels, read bounded LogQL pages, count lines by label or time, and export logs — across several Loki stands

Compares AI coding tool spend before and after a migration -- Cursor, Claude Code, GitHub Copilot, OpenCode, Codex CLI -- via an MCP server, real numbers from each vendor's own API or local logs.

MCP server for analyzing Perfetto traces with LLMs — query .pftrace files in PerfettoSQL via Claude Code or any MCP client

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

Enables Claude to discover and understand infrastructure-as-code drift by listing projects with drift, analyzing Terraform plan outputs, and providing remediation information.

Prediction stability engine for AI agents. Evaluate model stability, detect ghosts, probe any LLM for instability, monitor fleet drift. 20 tools + 1 resource. Works with Claude, Cursor, VS Code.

Sigma detection rule writing, validation, and pySigma-based multi-backend conversion (Splunk, Elastic, Wazuh, Kibana) via 3 MCP tools and 3 Claude Code skills, backed by a 61-rule production corpus across 11 MITRE ATT\&CK tactic categories.

Enables read-only debugging of Azure applications from GitHub Copilot, VS Code, and other MCP clients, with tools for resource health, changes, metrics, Application Insights telemetry, and logs for App Service, Container Apps, and AKS.

An MCP server that provides monitoring tools for Codex agents, allowing them to create and wait on conditions using commands, log files, file events, and custom probes, replacing polling loops with event-driven blocking.

Fetches Langfuse observability traces directly into a VS Code coding agent's context, enabling querying and viewing trace data through natural language.

Enables read-only inspection of local coding-agent sessions across Claude Code, OpenCode, Cursor, and Codex, including running status, topics, todos, and transcripts, without writing or sending messages.

Enables LLM assistants to analyze PostgreSQL query execution plans with EXPLAIN and receive structured reports highlighting performance bottlenecks, all through read-only database access.

Enables agents to check whether an execution trace contains the evidence needed for post-hoc causal reconstruction, retrieve individual requirement details, and list evidence requirements per failure class over MCP stdio. It works on files, directories, or inline JSON locally and never transmits or persists data.

Enables querying logs, traces, and metrics from multiple OpenObserve instances via MCP tools, with parallel execution, batching, and caching.

Live .NET runtime diagnostics for AI assistants. Ask Claude to diagnose memory leaks, GC pressure, LOH fragmentation, and thread starvation in any running .NET process — no code changes required.

MCP server for XXL-JOB Admin that enables AI assistants to manage scheduled jobs through natural language, including task lifecycle management, manual triggering, cron preview, and execution log retrieval.

DCL Trust Oracle is a deterministic AI audit layer, natively integrated with MCP, that evaluates LLM and agent outputs against configurable policies before and after action. Every verdict is written to a tamper-evident, hash-chained audit log storing only cryptographic metadata — never raw content — enabling privacy-first forensic review.

Provides transactional intelligence for AI agents, enabling safe tool execution with pre-flight invariant checks, sub-second filesystem snapshots/rollback, causal tracing, belief contradiction detection, and 15 native MCP tools for Claude Code.