wechat-mcp-server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| wechat_sessionsC | List recent WeChat chat sessions/conversations |
| wechat_historyB | Read chat history from a specific WeChat conversation |
| wechat_searchC | Search WeChat messages by keyword |
| wechat_contactsC | Search WeChat contacts |
| wechat_unreadC | Show unread WeChat sessions |
| wechat_new_messagesA | Get new WeChat messages since last check (incremental) |
| wechat_membersC | List members of a WeChat group |
| wechat_statsC | Get statistics for a WeChat chat |
| wechat_favoritesC | List WeChat favorites/bookmarks |
| wechat_distill_skillA | Distill personal communication style from chat history into an Agent Skills compliant SKILL.md. Args: chat_names: Comma-separated list of chat names to analyze message_limit: Maximum messages to analyze per chat output_format: 'markdown' (Agent Skills SKILL.md) or 'json' Returns: Agent Skills compliant skill data with YAML frontmatter, style rules, and few-shot examples |
| wechat_save_skillA | Distill and save skill to file as Agent Skills compliant SKILL.md. Args: chat_names: Comma-separated list of chat names output_path: Path to save the skill file (will create SKILL.md per Agent Skills spec) message_limit: Maximum messages per chat output_format: 'markdown' (Agent Skills SKILL.md) or 'json' Returns: Path to saved SKILL.md file or error message |
| wechat_start_listenerA | Start listening for new WeChat messages. The listener monitors database changes and buffers new messages. Use wechat_get_buffered_messages to retrieve them. Args: msg_dir: WeChat message directory path (e.g., "D:\xwechat_files\wxid_xxx\msg"). If not provided, will auto-detect. interval: Polling interval in seconds (default 0.5) Returns: Status message |
| wechat_stop_listenerA | Stop the message listener. Returns: Status message |
| wechat_listener_statusA | Get the current status of the message listener. Returns: Listener state and statistics |
| wechat_get_buffered_messagesA | Get buffered messages from the listener. Args: clear: Whether to clear the buffer after reading (default True) Returns: JSON array of buffered messages |
| wechat_build_sticker_libraryA | Build sticker library from chat history. Extracts sticker information including MD5, type, usage count. Args: chat_name: Chat name to analyze limit: Maximum messages to scan copy_files: Whether to copy sticker files to output_dir output_dir: Directory to copy sticker files (if copy_files=True) Returns: JSON with sticker library and usage patterns |
| wechat_search_stickersB | Search sticker library by name or description. Args: query: Search query limit: Maximum results to return Returns: JSON array of matching stickers |
| wechat_list_stickersA | List all stickers in the library. Returns: JSON object with all stickers |
| wechat_add_stickerB | Add a sticker to the library. Args: name: Name for the sticker (used in [sticker:name] placeholders) md5: MD5 hash of the sticker file_path: Path to the sticker file description: Description of the sticker tags: Comma-separated tags for searching Returns: Status message |
| wechat_parse_sticker_placeholderA | Parse sticker placeholders from text. Example: "Hello [sticker:dog]" -> [{"type": "text", "content": "Hello "}, {"type": "sticker", "name": "dog"}] Args: text: Text with sticker placeholders Returns: JSON array of parsed parts |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 20 tools
Tools have mostly distinct purposes, with slight overlap between message retrieval tools (history, new_messages, get_buffered_messages) but descriptions clarify differences. Sticker and skill tools are well-separated.
All tools start with 'wechat_', but some follow verb_noun pattern (wechat_add_sticker) while others are noun-only (wechat_contacts, wechat_history), causing minor inconsistency.
20 tools is appropriate for a WeChat integration, covering contacts, sessions, messages, stickers, skills, and listener functionality without being overwhelming.
Missing core functionality like sending messages or modifying contacts, which are expected for a chat server. Focus is on data retrieval and analysis, leaving significant gaps.