"Understanding 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.

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 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.