MCP Server Builder
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
Review a Shadow MCP target, approve an explicit audience, and safely onboard and distribute it through the Speakeasy AI Control Plane Platform MCP.
$ npx skills add speakeasy-api/gram --skill review-shadow-mcp -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install speakeasy-api/gram review-shadow-mcp --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .claude/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/review-shadow-mcp .claude/skills/review-shadow-mcp && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "review-shadow-mcp" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcp into .claude/skills/review-shadow-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-shadow-mcp", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcpType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add speakeasy-api/gram --skill review-shadow-mcp -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install speakeasy-api/gram review-shadow-mcp --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .agents/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/review-shadow-mcp .agents/skills/review-shadow-mcp && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "review-shadow-mcp" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcp into .agents/skills/review-shadow-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-shadow-mcp", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add speakeasy-api/gram --skill review-shadow-mcp -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install speakeasy-api/gram review-shadow-mcp --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/review-shadow-mcp .cursor/skills/review-shadow-mcp && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "review-shadow-mcp" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcp into .cursor/skills/review-shadow-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-shadow-mcp", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/speakeasy-api/gram.git --path server/internal/plugins/platform_mcp_skills/review-shadow-mcp--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add speakeasy-api/gram --skill review-shadow-mcp -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install speakeasy-api/gram review-shadow-mcp --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/review-shadow-mcp .gemini/skills/review-shadow-mcp && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "review-shadow-mcp" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcp into .gemini/skills/review-shadow-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-shadow-mcp", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install speakeasy-api/gram review-shadow-mcpInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add speakeasy-api/gram --skill review-shadow-mcp -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .github/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/review-shadow-mcp .github/skills/review-shadow-mcp && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "review-shadow-mcp" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcp into .github/skills/review-shadow-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-shadow-mcp", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add speakeasy-api/gram --skill review-shadow-mcp -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install speakeasy-api/gram review-shadow-mcp --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/speakeasy-api/gram.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/server/internal/plugins/platform_mcp_skills/review-shadow-mcp .opencode/skills/review-shadow-mcp && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "review-shadow-mcp" agent skill from https://github.com/speakeasy-api/gram/tree/main/server/internal/plugins/platform_mcp_skills/review-shadow-mcp into .opencode/skills/review-shadow-mcp/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "review-shadow-mcp", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
review-shadow-mcpReview a Shadow MCP target, approve an explicit audience, and safely onboard and distribute it through the Speakeasy AI Control Plane Platform MCP.
Review Shadow MCP is an agent skill from speakeasy-api/gram. Review a Shadow MCP target, approve an explicit audience, and safely onboard and distribute it through the Speakeasy AI Control Plane Platform MCP.
Its SKILL.md is about 1.5k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering MCP servers. It works with Model Context Protocol. The repository describes itself as: Securely scale AI usage across your organization. A single stack to Connect, Secure, Observe and Distribute agents, MCPs, and Skills within your company. The licence is AGPL-3.0.
9 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 1378037. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md.
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Review Shadow MCP loads about 1.5k tokens when it runs. Until then it costs about 41 tokens; SKILL.md has 816 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from speakeasy-api/gram at commit 1378037, republished under its AGPL-3.0 licence (© speakeasy-api). 816 words, ~1,486 tokens.
.claude/skills/review-shadow-mcp/SKILL.md (or your agent's skills folder).Use this workflow only through an authenticated Speakeasy AI Control Plane (AICP) Platform MCP connected as an external administrator. It follows the guarded AICP dashboard outcome: review one observed target, make an explicit audience decision, optionally onboard an approved remote target, and distribute the ready MCP to one exact plugin. It is not available to managed project assistants or the member-safe catalogue. Installing this package grants no organization access or authority.
list_projects. If its truncated result is true, report that project discovery is incomplete and hand off to the AICP dashboard; otherwise present the eligible projects and ask the user to select one exact project. Retain both its returned ID for Shadow and plugin inventory tools and its slug for readiness and distribution tools.list_shadow_mcp_inventory with that exact project ID. Present only its bounded summaries and ask the user to select one exact opaque target reference. Call get_shadow_mcp_review with the same project ID and target reference.list_plugin_assignments for the exact project. If the user intends to match an existing plugin, ask them to name it and call get_plugin; use only a complete, untruncated assignment set. Ask the user to select exact server-returned audience references and provide a bounded rationale. Stop and use the AICP dashboard if the required assignments are truncated or incomplete.get_shadow_mcp_review and any audience references before presenting the bounded review evidence, every gap, the proposed allow or deny decision, the complete selected audience, and the rationale. Ask for explicit confirmation of that exact fresh project, target, decision, audience, and rationale, then immediately call decide_shadow_mcp_access with the immediately preceding expected_version, a fresh idempotency key, and confirmed: true. If it conflicts or a reference expires, re-read and re-present the changed state, then obtain confirmation again. An allow requires one or more selected audience references; a deny has none.get_shadow_mcp_review again and report the committed live review. The review result does not expose a raw remote URL or an onboarding action, so never reconstruct either. To onboard an approved target, hand off to the AICP dashboard and stop until the user confirms dashboard setup is complete.find_mcp with an explicit user-provided query, present the bounded configured MCP matches, and ask the user to select one exact result. Call get_mcp for that exact MCP and continue only when it returns a Platform-managed registration ID. Call get_mcp_readiness with the exact project slug and registration ID and force: true; continue only when fresh evidence says the MCP is ready.list_plugins, present the exact project plugins, and ask the user to choose one. Call get_plugin for that exact plugin and require its complete, untruncated assignment set. Compare the whole set with the approved audience and current distribution_admission; keep publication state separate. If assignments must change, refresh list_plugin_assignments, present the complete replacement and state that it changes who receives every MCP server in that plugin, not only this target. Ask for explicit confirmation, then call set_plugin_assignments with the immediately preceding assignment_version as expected_assignment_version, a fresh idempotency key, and confirmed: true. Re-read get_plugin after the mutation.distribute_mcp_to_plugin. If it returns a denial or conflict, re-read get_shadow_mcp_review and get_plugin and return to user review without automatically changing or renewing the approval.get_plugin and get_shadow_mcp_review again. Report the live attachment, distribution admission, and publication evidence separately. Do not claim that users have the MCP unless the returned live state supports that conclusion.The approval, registration, assignment, and distribution confirmations are separate decisions. Browser setup and authorization are separate secure handoffs. Preserve each boundary even when the user wants to complete the whole workflow.
© speakeasy-api, AGPL-3.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in server/internal/plugins/platform_mcp_skills/review-shadow-mcp of speakeasy-api/gram.
Open the folder on GitHubat commit 1378037
Review Shadow MCP next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Review Shadow MCP this skillspeakeasy-api/gram | 273 | — | ~1.5k | Automated safety check: Pass | AGPL-3.0 | |
| MCP Server Builderanthropics/skills | 180k | 63 repos | ~2.3k | Automated safety check: Pass | Apache-2.0 | |
| MCP Server BuildershareAI-lab/learn-claude-code | 78k | 5 repos | ~1.2k | Automated safety check: Pass | MIT | |
| MCP Integration for Pluginsanthropics/claude-plugins-official | 38k | 11 repos | ~3.1k | Automated safety check: Pass | Apache-2.0 | |
| Crush Configurationcharmbracelet/crush | 29k | — | ~3.7k | Automated safety check: Pass | Custom licence | |
| Context Mode Output Sandboxmksglu/context-mode | 26k | — | ~4.1k | Automated safety check: Pass | Custom licence |
anthropics/skills
Guides the design and implementation of Model Context Protocol servers in TypeScript or Python, from tool naming and error messages to evaluation.
shareAI-lab/learn-claude-code
Walks through building MCP servers in Python or TypeScript that expose tools, resources and prompts to Claude, with templates, registration and testing.
anthropics/claude-plugins-official
Explains how to bundle Model Context Protocol servers in a Claude Code plugin, covering config files, stdio, SSE, HTTP and WebSocket server types, and authentication.
charmbracelet/crush
Explains how to configure the Crush coding agent with crushrc or crush.json, covering providers, models, LSPs, MCP servers, hooks, permissions and config precedence.
mksglu/context-mode
Routes large command, file, API and browser output through context-mode tools so only the needed result enters the agent's context, instead of dumping it via Bash.
warpdotdev/warp
Migrates the compatible subset of settings and global file-based MCP servers from the Warp desktop app into Warp Agent CLI without exposing credentials or state.
speakeasy-api/gram
A skill your agent uses when automating the Speakeasy dashboard in a browser, capturing screenshots, inspecting pages.
speakeasy-api/gram
A skill your agent uses when adding, changing, restyling, reviewing, validating, or previewing a Speakeasy transactional email, in Go or in LMX/MJML — a template<name.go, a TemplateKey constant, a…
speakeasy-api/gram
A skill your agent uses when adding, changing, or styling UI in client/admin (the Speakeasy admin dashboard) that touches shadcn/ui — a button, dialog, table, sidebar, badge, select, tabs, tooltip…
speakeasy-api/gram
A skill your agent uses when adding, editing, reviewing, testing, or locating a reviewed skill distributed with the Platform MCP plugin; triggers include "Platform MCP skill", "platformmcpskills"…
speakeasy-api/gram
A skill your agent uses when changing or reviewing Speakeasy ClickHouse schemas, migrations, queries, inserts, access principals, bootstrap SQL, Cloud compatibility, partial migration failures, or…
speakeasy-api/gram
A skill your agent uses when gating a feature behind a flag, dogfooding or gradually rolling out a change, choosing between productfeatures and PostHog feature flags, adding or checking a product…
Works with
Categories
Review a Shadow MCP target, approve an explicit audience, and safely onboard and distribute it through the Speakeasy AI Control Plane Platform MCP. Review Shadow MCP is an agent skill from speakeasy-api/gram. Review a Shadow MCP target, approve an explicit audience, and safely onboard and distribute it through the Speakeasy AI Control Plane Platform MCP.
Review Shadow MCP fits situations like: tasks that involve MCP servers.
Run `npx skills add speakeasy-api/gram --skill review-shadow-mcp -a claude-code`. Or copy the skill folder (server/internal/plugins/platform_mcp_skills/review-shadow-mcp in speakeasy-api/gram) into .claude/skills/review-shadow-mcp in your project. Claude Code loads it when a task matches its description.
Run `npx skills add speakeasy-api/gram --skill review-shadow-mcp -a codex`. Or copy the skill folder (server/internal/plugins/platform_mcp_skills/review-shadow-mcp in speakeasy-api/gram) into .agents/skills/review-shadow-mcp in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add speakeasy-api/gram --skill review-shadow-mcp -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/review-shadow-mcp, .gemini/skills/review-shadow-mcp, .github/skills/review-shadow-mcp and .opencode/skills/review-shadow-mcp in your project.
SKILL.md names no scripts, command-line tools or credentials: Review Shadow MCP is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
Review Shadow MCP is published under the AGPL-3.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 1.5k tokens (SKILL.md is roughly 5.9k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with Review Shadow MCP: MCP Server Builder (anthropics/skills, 180k stars), MCP Server Builder (shareAI-lab/learn-claude-code, 78k stars), MCP Integration for Plugins (anthropics/claude-plugins-official, 38k stars) and Crush Configuration (charmbracelet/crush, 29k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
speakeasy-api (a GitHub organization) maintains it in speakeasy-api/gram, which has 273 GitHub stars. The repository holds 39 skills in this directory. The repository was last updated on October 9, 2026.
Source: speakeasy-api/gram on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.