# Taplio MCP MCP Server > **Taplio MCP MCP Server** is a hosted, multitenant Model Context Protocol (MCP) server run by **MewCP** (https://mewcp.com), giving AI agents managed access to Taplio MCP. > > MewCP takes care of all MCP infrastructure for you — credential storage, OAuth flows, > token refresh, and production-grade auto-scaling — so your AI agents can connect to > third-party services and run freely without you managing any MCP server yourself. > > Server page: https://mewcp.com/mcp/taplio-mcp > MewCP docs: https://docs.mewcp.com > Full catalog: https://mewcp.com/llms.txt --- ## About Taplio helps LinkedIn creators plan and grow their presence by generating posts, scheduling content, managing drafts, discovering viral post ideas, and tracking engagement analytics to improve audience reach. --- ## Details - Server ID: `taplio-mcp` - Version: 0.1.0 - Tools: 35 - Authentication: OAuth, managed by MewCP - Transport: http --- ## Access The gateway URL below serves your **entire MewCP toolset**, not this server on its own. Pasting a config snippet is not enough — Taplio MCP has to be in the toolset first. In order: 1. Add Taplio MCP to your toolset at https://mewcp.com/mcp/taplio-mcp 2. Connect your Taplio MCP account (OAuth); MewCP stores the credential and attaches it to each call 3. Copy your MewCP API key from the dashboard (Developer) 4. Configure your client with the snippet for it below Once connected, an agent does **not** see this server's tools as top-level tools. It sees four meta-tools and reaches everything through them: - `search(query)` — find tools by keyword across the toolset - `get_schema(tools)` — full description and arguments for the tools you picked - `list_accounts(provider)` — only when one app has several connected accounts - `call_tool(server_maskedId, tool_name, args)` — execute So the list below is what `search` can return for this server, not a set of callable tool names on their own. --- ## Tools (35) Descriptions are truncated to 160 characters; call `get_schema` for the full text and the argument schema. Where a tool is annotated, its type is shown — treat `destructive` as irreversible. - `list_posts` _(read)_ — List the user's LinkedIn posts, newest first: posts created in Taplio (status scheduled, sending, or sent) plus posts published directly on LinkedIn, which… - `get_post` _(read)_ — Fetch a single LinkedIn post by id — either a Taplio post id or the LinkedIn urn list_posts returns for a post published directly on LinkedIn, which resolves… - `list_drafts` _(read)_ — List the user's unpublished LinkedIn post drafts. Use it to review the content pipeline or find a draft to edit, schedule, or publish. - `get_draft` _(read)_ — Fetch a single LinkedIn post draft by id. - `create_draft` _(write)_ — Create a new LinkedIn post draft (unpublished). Attach media by passing media_ids (from list_media, or a media_id from create_media_upload_url whose bytes you… - `update_draft` _(write)_ — Update the content of an existing LinkedIn post draft, optionally attaching media by media_ids (from list_media, or a media_id from create_media_upload_url… - `attach_media_from_url` _(write)_ — Attach an image or video to a LinkedIn post draft before scheduling or publishing, by giving a public https url. Calls the Taplio API (see… - `create_media_upload_url` _(write)_ — Get a one-time presigned S3 URL to upload an image, video, GIF, or PDF, then attach it with update_draft's media_ids. Two-step flow: (1) call this with the… - `list_media` _(read)_ — List media you've already uploaded to Taplio (id, type, public url, filename), most recent first. Optionally filter by a filename substring with query. Use it… - `schedule_draft` _(write)_ — Schedule a LinkedIn post draft to be published automatically at a future time. - `unschedule` _(write)_ — Unschedule a scheduled LinkedIn post, returning it to drafts so you can edit, reschedule, or delete it. - `publish_draft` _(destructive)_ — Publish a LinkedIn post draft to LinkedIn immediately. This goes live now and cannot be undone. - `delete_draft` _(destructive)_ — Permanently delete a LinkedIn post draft. - `search_inspiration` _(read)_ — Search LinkedIn posts from other creators to use as inspiration. Use it before drafting to ground new posts in proven formats and angles from other creators.… - `get_analytics_overview` _(read)_ — Get the user's LinkedIn analytics overview (followers, impressions, engagement). Defaults to today's overview when no date range is given. Also a post-creation… - `get_post_analytics` _(read)_ — List the user's per-post LinkedIn analytics (impressions, likes, comments, shares) and each post's media_type (text, image, video, document or article; absent… - `get_me` _(read)_ — Read this first to orient. Returns the user's identity and content preferences so you can tailor output to them and recognize their own posts: their display… - `find_posts_to_comment` _(read)_ — Find LinkedIn posts worth commenting on, from one of three sources: the user's own recent posts, a curated feed of hand-picked profiles, or a personalized… - `list_comment_feeds` _(read)_ — List the curated feeds available for engagement, each a hand-picked set of profiles with the number of profiles it tracks. The name returned here is exactly… - `find_comments_to_reply` _(read)_ — Find comments on LinkedIn posts that are still worth a reply: comments the user already answered, wrote themselves, or hid are filtered out. Every comment… - `list_comment_drafts` _(read)_ — List the user's LinkedIn comment drafts, newest first. A draft keeps the same record for its whole life, so this is also the queue and the history: status… - `get_comment_draft` _(read)_ — Fetch a single LinkedIn comment draft by id. This is how you confirm what a commit actually did: status is draft (still editable, nothing queued), pending… - `create_comment_draft` _(write)_ — Draft a LinkedIn comment on someone else's post, or a reply to a comment on it. The draft is unpublished: nothing reaches LinkedIn until commit_comment_draft,… - `update_comment_draft` _(write)_ — Rewrite the text of a LinkedIn comment draft. Only a draft still in status draft can be edited: once it is committed it is queued or already posted, and the… - `commit_comment_draft` _(destructive)_ — Commit a comment draft, which SCHEDULES the comment to be posted on LinkedIn under the user's name, on someone else's post. The comment is NOT live when this… - `cancel_comment_draft` _(destructive)_ — Cancel a committed comment before it is sent, so it never reaches LinkedIn. Returns the draft with status cancelled and a failure_reason. A draft that was… - `send_connection_request` _(write)_ — Ask to connect with someone on LinkedIn, by their public username (the last part of their profile url). The invitation is not sent during this call: it joins… - `list_connection_requests` _(read)_ — List every connection request this account has queued, newest first, whatever became of each one: pending while it waits in the send queue, sent once it left,… - `get_connection_request` _(read)_ — Read back the latest connection request this account queued for a username: pending while it waits in the send queue, sent once it left, failed or cancelled… - `cancel_connection_request` _(destructive)_ — Cancel a connection request before it is sent, so the invitation never reaches LinkedIn. Returns the request with status cancelled and a failure_reason. A… - `like_post` _(write)_ — Like a LinkedIn post or a comment on one. `post_urn` takes the `post_urn` of a find_posts_to_comment result, the urn inside a list_posts `url`, the… - `get_post_like` _(read)_ — Read back the latest like this account queued for a post or a comment: pending while it waits in the send queue, liked once it went out, failed or cancelled… - `cancel_like` _(destructive)_ — Cancel a like before it is sent, so it never reaches LinkedIn. Returns the like with status cancelled and a failure_reason. A like that was already sent,… - `pick_media` _(write)_ — Open an interactive panel listing the media ALREADY in the user library (images, videos, GIFs, PDFs) as a thumbnail grid; clicking a tile attaches it to the… - `upload_media` _(write)_ — Open an interactive panel with a drop zone plus a file chooser, for a NEW file from the user device: the dropped or chosen image, video or PDF is uploaded to… --- ## Connect Gateway URL: https://gateway.mewcp.com/personal/mcp Every request carries one header: Authorization: Bearer Replace `API_KEY` with your own key from the dashboard (Developer). ## Apps ### Claude Desktop Mac & Windows app - macOS: `~/Library/Application Support/Claude/claude_desktop_config.json` - Windows: `%APPDATA%\Claude\claude_desktop_config.json` ```json { "mcpServers": { "mewcp": { "command": "npx", "args": [ "-y", "mcp-remote@latest", "https://gateway.mewcp.com/personal/mcp", "--header", "Authorization:${AUTH_HEADER}" ], "env": { "AUTH_HEADER": "Bearer API_KEY" } } } } ``` Already have an "mcpServers" section in your config? Just add the server entry inside it. 1. Open Claude Desktop → Settings → Developer → "Edit Config" 2. Paste the snippet inside the outer { } of the config file (merge with your existing "mcpServers" section if you have one) 3. Save the file, then quit Claude Desktop completely and reopen it 4. Start a new conversation — your tool will be available ### VS Code Copilot / Cline - Command Palette → "MCP: Open User Configuration" (opens mcp.json). For one project only, use .vscode/mcp.json instead. ```json { "mcp.servers": { "mewcp": { "type": "http", "url": "https://gateway.mewcp.com/personal/mcp", "headers": { "Authorization": "Bearer API_KEY" } } } } ``` Already have a "servers" section in your mcp.json? Just add the server entry inside it. 1. Open VS Code → Command Palette (Cmd+Shift+P / Ctrl+Shift+P) 2. Run "MCP: Open User Configuration" to open your mcp.json 3. Paste the snippet and save 4. Start the server when prompted (or from the MCP servers view) and use it in Copilot Chat ### Cursor AI-first editor - macOS: `~/.cursor/mcp.json` - Windows: `%USERPROFILE%\.cursor\mcp.json` ```json { "mcpServers": { "mewcp": { "url": "https://gateway.mewcp.com/personal/mcp", "headers": { "Authorization": "Bearer API_KEY" } } } } ``` Already have an "mcpServers" section in your mcp.json? Just add the server entry inside it. 1. Open Cursor → Settings → Cursor Settings → MCP 2. Click "Add new global MCP server" 3. Paste the snippet and save 4. Restart Cursor ### Codex OpenAI's CLI agent - Add the snippet to your Codex MCP config or your standard MCP config file for the CLI tool you use. ```json { "mcpServers": { "mewcp": { "type": "http", "url": "https://gateway.mewcp.com/personal/mcp", "headers": { "Authorization": "Bearer API_KEY" } } } } ``` Codex generally reads a standard MCP server block, so you can add this alongside your other configured servers. 1. Open your Codex MCP config or project-level config file 2. Paste the MewCP server block inside the config JSON/TOML structure your tool expects 3. Save the file and restart Codex 4. Verify the tool is available inside a fresh session ### Claude Code Anthropic's CLI agent - ~/.claude.json (user scope) or .mcp.json in your project root — create it if it doesn't exist. Or skip the file and use the CLI command below. ```json { "mcpServers": { "mewcp": { "type": "http", "url": "https://gateway.mewcp.com/personal/mcp", "headers": { "Authorization": "Bearer API_KEY" } } } } ``` Already have an "mcpServers" section in your config? Just add the server entry inside it. 1. Open ~/.claude.json (or .mcp.json in your project root) in a text editor 2. Paste the snippet inside the outer { } (merge with your existing "mcpServers" section if you have one) 3. Save the file and start (or restart) Claude Code 4. Or skip the file entirely and run the CLI command below instead ### OpenCode Open-source terminal agent - ~/.config/opencode/opencode.json (global) or opencode.json in your project root — create it if it doesn't exist. ```json { "$schema": "https://opencode.ai/config.json", "mcp": { "mewcp": { "type": "remote", "url": "https://gateway.mewcp.com/personal/mcp", "enabled": true, "headers": { "Authorization": "Bearer API_KEY" } } } } ``` Already have an "mcp" section in your opencode.json? Just add the server entry inside it. 1. Open ~/.config/opencode/opencode.json (or opencode.json in your project root) in a text editor 2. Paste the snippet inside the outer { } (merge with your existing "mcp" section if you have one) 3. Save the file and start (or restart) OpenCode ### OpenClaw Self-hosted agent gateway - ~/.openclaw/openclaw.json — create it if it doesn't exist. ```json { "mcp": { "servers": { "mewcp": { "transport": "streamable-http", "url": "https://gateway.mewcp.com/personal/mcp", "enabled": true, "headers": { "Authorization": "Bearer API_KEY" } } } } } ``` Already have an "mcp" section in your openclaw.json? Just add the server entry inside "servers". 1. Open ~/.openclaw/openclaw.json in a text editor 2. Paste the snippet inside the outer { } (merge with your existing "mcp" section if you have one) 3. Save the file and restart OpenClaw ### Antigravity Google's agentic IDE - ~/.gemini/config/mcp_config.json (global) or .agents/mcp_config.json (workspace-local) — create it if it doesn't exist. ```json { "mcpServers": { "mewcp": { "serverUrl": "https://gateway.mewcp.com/personal/mcp", "headers": { "Authorization": "Bearer API_KEY" } } } } ``` Already have an "mcpServers" section in your config? Just add the server entry inside it. Remote servers must use the "serverUrl" field — the legacy "url"/"httpUrl" fields aren't supported. 1. In the editor's agent side panel, click "…" → "MCP Servers" → "Manage MCP Servers" → "View raw config" (Antigravity CLI: type /mcp instead to open the Interactive MCP Manager) 2. Paste the snippet inside the outer { } (merge with your existing "mcpServers" section if you have one) 3. Save the file — the server connects automatically ### Hermes Nous Research's CLI agent - config.yaml in your Hermes config directory (~/.hermes) — add this under a top-level "mcp_servers:" key. ```yaml mcp_servers: mewcp: url: "https://gateway.mewcp.com/personal/mcp" headers: Authorization: "Bearer API_KEY" ``` Already have an "mcp_servers" section in your config.yaml? Just add the server entry inside it. 1. Open config.yaml in your Hermes config directory 2. Paste the snippet under the top-level "mcp_servers:" key (merge with existing entries if you have any) 3. Save the file, then run /reload-mcp in Hermes (or start a fresh session) 4. Ask Hermes "Tell me which MCP-backed tools are available right now" to confirm it connected ### DeepSeek Harness DeepSeek's agent harness - cordis.yml in your DSH project — or the patch file you mount plugins from. ```yaml - id: mcp-mewcp name: '@deepseek-ai/dsh-mcp-client' config: serverName: mewcp transport: streamable-http url: https://gateway.mewcp.com/personal/mcp headers: Authorization: "Bearer API_KEY" ``` One plugin instance = one MCP server. Add this entry to your plugin list; don't nest it inside another entry. 1. Open cordis.yml (or your patch file) in your DSH project 2. Paste the entry into your plugin list, keeping the leading dash and indentation 3. Restart DSH (or let HMR reload) — tools register as mcp__mewcp__ 4. Verify with: dsh web --dump-config | grep -A3 mcp ## SDKs ### Python fastmcp client ```python import asyncio from fastmcp import Client from fastmcp.client.transports import StreamableHttpTransport SERVER_URL = "https://gateway.mewcp.com/personal/mcp" API_KEY = "API_KEY" transport = StreamableHttpTransport( url=SERVER_URL, headers={ "Authorization": f"Bearer {API_KEY}", } ) async def main(): client = Client(transport) async with client: tools = await client.list_tools() print(tools) asyncio.run(main()) ``` 1. Install fastmcp: pip install fastmcp 2. Copy the snippet into your project 3. Replace API_KEY with your key from the dashboard 4. Run your script ### TypeScript MCP SDK ```typescript import { Client } from "@modelcontextprotocol/sdk/client/index.js"; import { StreamableHTTPClientTransport } from "@modelcontextprotocol/sdk/client/streamableHttp.js"; const SERVER_URL = "https://gateway.mewcp.com/personal/mcp"; const API_KEY = "API_KEY"; const transport = new StreamableHTTPClientTransport(new URL(SERVER_URL), { requestInit: { headers: { Authorization: `Bearer ${API_KEY}`, }, }, }); const client = new Client({ name: "mewcp-client", version: "1.0.0" }); await client.connect(transport); const tools = await client.listTools(); console.log(tools.tools.map((t) => t.name)); ``` 1. Install: npm install @modelcontextprotocol/sdk 2. Copy the snippet into your project 3. Replace API_KEY with your key from the dashboard 4. Run with Node 18+ as an ES module (e.g. npx tsx script.ts)