"Île-de-France Mobilités" matching MCP servers:

Je dois répondre en JSON avec name et description. Name = "jevmem" (le nom du serveur MCP publié). Description : décrit ce que le serveur permet, sans répéter le nom. Par exemple : "Saves decisions, rules, bugs, to-dos and dead ends from Claude Code and Cursor chats into a versioned JEVMEM.md file in the repository, then brings the relevant lines back in later sessions and checks tool calls against saved rules before they run." Je dois vérifier : ne pas citer de personne/mainteneur/organisation. Ne pas répéter le nom. Deux phrases max. Éviter de mentionner "jevmem" comme nom. Je peux dire "Saves..." sans nom. Ça mentionne JEVMEM.md, ce n'est pas le nom du serveur mais le fichier, c'est autorisé ? La consigne : la description ne doit pas reprendre le nom. Le nom est "jevmem" ; "JEVMEM.md" contient jevmem. Mieux éviter. Je vais dire "a markdown memory file in the repository". Éviter aussi les noms d'organisations (TypeSafe, Anthropic, Claude Code...). Claude Code est un produit, pas une personne/organisation. Mais prudence : ne pas citer de mainteneur ou d'organisation. Je peux dire "coding-agent chats". La description doit dire ce que le serveur permet. Je vais faire deux phrases.

Integra agentes de desenvolvimento ao sistema Gestão de Tarefas, permitindo gerenciar projetos, demandas, sprints e tarefas com suporte a fila offline e sincronização posterior.

A read-only server that exposes Synergy/DE documentation as tools and resources for searching, retrieving, and browsing topics. It features full-text search, version support, and optimized content chunking for seamless integration with LLMs and MCP clients.

Enables AI agents to scan code or text content for hardcoded API keys, passwords, tokens, and private keys, reporting each finding by type, confidence, key name, and position. Secret values are never returned, so credentials can be located and addressed without leaving the machine.

Compares the key names across .env file contents supplied by an agent and reports which keys are missing from which file, supporting auto, manual, and template comparison modes. Only key names are returned, never values, and the server reads no files or network resources of its own.

Enables MCP agents to extract every IPv4/IPv6 address, CIDR block, and MAC address from text, normalize and classify them by scope, and report ambiguous forms with their reasons.

Enables agents to pull every file path out of supplied document content — imports, asset references, and config values — and get each one classified as a file, relative, absolute, or URL with its line and column. It works purely on text passed in, reading no files and making no network requests, so codebases can be audited for references that still point at something.

Enables MCP agents to extract every date and timestamp from supplied text content and return each one’s notation, resolved epoch instant, and source line and column, with options for deduplication, date ordering, kind filtering, and result limits.

Provides a tool to extract and validate regex patterns from text content, including flags, positions, and ReDoS risk assessment. Enables AI agents to identify potentially dangerous regular expressions in code or files without needing filesystem access.

Enables agents to extract hardcoded numeric values from supplied text or code across many data and source-code formats, returning values in document order with notation and available line/column positions. Supports deduplication and truncated result sets.

Enables users to browse, search, filter, and select project skills through an interactive interface, then confirms the selection so the chosen instructions and customizations are applied to the site project.

Enables AI agents to submit npm, PyPI, Go, or Maven packages and manifests to the free OSV.dev database and receive per-package and per-advisory results with CVE mappings, CVSS scores, severities, and the versions that fix each issue. It also supports filtering by minimum severity, de-duplicating alias advisories, and machine-readable error/warning rows for CI gates and upgrade recommendations.

Enables coding agents to list, search, and read a curated Shopware developer and merchant knowledge base offline as plain Markdown files, without network access or an API key.

Enables AI coding agents to list, read, create, update, delete, and render PlantUML and Mermaid diagrams, and check them against the actual codebase to detect architecture drift.

Enables using DeepSeek models as a small, cheap supervised worker from any MCP-compatible client, providing fast flash and deep reasoning tools for bounded tasks.

Publish forms from your agent and read their submissions. Also validates and simulates Formhaus JSON form definitions offline.

MCP server for PCSX2 and other emulators that speak the PINE protocol. Read and write 8/16/32/64-bit emulator memory and control save states for PlayStation-family emulation.

An MCP server that exposes PPSSPP — the PlayStation Portable emulator — to any MCP-compatible client (Claude Desktop, Claude Code, etc.) via PPSSPP's built-in WebSocket debugger interface. Read and write PSP memory, drive games with button input, capture screenshots, set CPU breakpoints, inspect MIPS Allegrex registers — all through a clean tool interface. No bridge plugin needed; PPSSPP's debugg

Explains known developer errors offline and deterministically (CORS, ESM/CommonJS, npm ERESOLVE, Next.js builds, Postgres connection and DATABASE_URL errors). One tool, explain_error; no LLM, no network.

An MCP server that enables AI coding assistants to interact with a local Airflow cluster via its REST API for triggering DAG runs, monitoring status, reading logs, and diagnosing errors.

MCP server for the nagi-ledger audit ledger and guardrail toolkit, exposing tools to record and annotate AI agent actions, subagent dispatches, and known dead ends, plus query session reports and statistics.

An MCP server that exposes tools for issuing scoped agent credentials, delegating narrower child credentials, handling approvals, revoking task trees, and retrieving audit trails and evidence packets.

A code review tool that generates detailed HTML review documents by comparing branches or commits, with author filtering and intelligent analysis.

Fresh, source-verified docs for building MCP servers and Claude agents, served to your AI coding agent over MCP. Each document is stamped with its source URL and last-verified date.

MCP server for BizHawk, the multi-system emulator. Drive NES, SNES, GB/GBC/GBA, Genesis, N64, PSX, Saturn and more through one Lua bridge — memory r/w across named domains, joypad input, frame-advance, screenshot, save/load state.

Enables AI assistants to build PayRetailers cross-border payment integrations accurately by providing official documentation, endpoint specs, country-specific payload validation, webhook guidance, and integration prompts as MCP resources, tools, and prompts.

Optimizes REST API calls for AI agents by returning compact schemas instead of full responses, allowing agents to fetch only needed fields via jq masks, reducing token consumption by up to 50x.

Translates a lockfile diff into a human-readable upgrade plan. For every dependency bump (npm or PyPI) returns semver class, breaking changes from GitHub release notes, CVEs fixed in the range, migration guide links, and a clear per-package recommendation. Bulk tool ranks up to 50 package changes in parallel by risk (security > caution > review > likely-safe > safe).

Model Context Protocol server for AI Canvas. Search, inspect, and install open-source React and Tailwind components from the aicanvas.me registry directly in your AI editor.

Email for AI agents. Send and receive as markdown with human oversight.