Context Doctor vs Prompts.chat MCP
A side-by-side look at the Context Doctor and Prompts.chat MCP MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
Verdict: choose Context Doctor for conversational ai work as a local process; choose Prompts.chat MCP for conversational ai as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Context Doctor when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You want tools like
profile_context, optimize_context, pack_context.
Choose Prompts.chat MCP when
- You need dedicated capabilities in the Conversational AI domain.
- You prefer a local stdio subprocess transport.
- You have the keys it needs:
PROMPTS_API_KEY, PROMPTS_QUERY. - You want tools like
search_prompts, get_prompt.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | ||
|---|---|---|
| Category | Conversational AI | Conversational AI |
| Quality signal | 56/100 · Good | 55/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | Not declared | Not declared |
| Pricing | Not declared | Not declared |
| Required env vars | None listed | PROMPTS_API_KEYPROMPTS_QUERY |
| Verified owner | Community listing | Community listing |
| GitHub stars | 2 | 36 |
| Directory activity | 1 views 0 installs 0 upvotes | 3 views 0 installs 0 upvotes |
| Tools | 4 | 2 |
| Full listing | View Context Doctor | View Prompts.chat MCP |
Tools & capabilities
Context Doctor tools 4
profile_contextToken breakdown by category, largest messages, findings with estimated savings. Takes either `conversation` (full JSON or text) or `sketch` (turns + large/repeated blocks, for chat apps)optimize_contextRewrites the conversation: dedupe, trim stale tool results, strip base64, optional history pruningpack_contextOnly the chunks of large local files or folders (or passed `text`) that a question needs, within `max_tokens`; outline without a query; `ids` to fetch more. Reads no files over HTTPcontext_best_practicesCurated checklist, optionally specialized for Anthropic / OpenAI
Prompts.chat MCP tools 2
search_promptsSearch for AI prompts by keyword. Returns matching prompts with title, description, content, author, category, and tags.get_promptGet a prompt by ID. If the prompt contains template variables (like ${variable} or ${variable:default}), you may need to provide values for them.
Ready-to-paste client configs
Paste either block (or both) into your client config, e.g. claude_desktop_config.json or ~/.cursor/mcp.json. We only show a config when the install command is confirmed.
Context Doctor
{
"mcpServers": {
"context-doctor": {
"command": "npx",
"args": [
"-y",
"context-doctor"
]
}
}
}
Prompts.chat MCP
{
"mcpServers": {
"prompts-chat-mcp": {
"command": "npx",
"args": [
"-y",
"@fkadev/prompts.chat-mcp"
],
"env": {
"PROMPTS_API_KEY": "YOUR_PROMPTS_API_KEY_HERE",
"PROMPTS_QUERY": "YOUR_PROMPTS_QUERY_HERE"
}
}
}
}
Frequently asked questions
Context Doctor is categorized under Conversational AI and uses a local stdio subprocess. Prompts.chat MCP belongs to Conversational AI and uses a local stdio subprocess. Pick Context Doctor for conversational ai work and Prompts.chat MCP for conversational ai.
Copy the mcpServers block from the config section on this page into your client's config (for example claude_desktop_config.json or ~/.cursor/mcp.json), then fully restart the client.
Context Doctor has no declared pricing — check the project's own site. Prompts.chat MCP has no declared pricing — check the project's own site. If a server needs environment variables such as API keys, define them under the env key in your client's MCP config.
Yes. MCP clients support multiple servers: add context-doctor and prompts-chat-mcp as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Context Doctor has a quality signal of 56/100 (Good) with 1 views, 0 installs and 2 GitHub stars. Prompts.chat MCP has 55/100 (Good) with 3 views, 0 installs and 36 GitHub stars.