Fetch vs Sifter
A side-by-side look at the Fetch and Sifter MCP servers: transport, auth, tools, quality signals, and the config to install either one in Claude, Cursor, Windsurf or VS Code.
SifterSearch & Data Extraction · Local subprocess (stdio)Structure any document, query it like a database. Open-source extraction engine that turns any document into typed, schema-defined records, queryable in natural language from Claude, ChatGPT, Gemini, or any MCP client.55GoodAuth: api key requiredVerdict: choose Fetch for search & data extraction work as a local process; choose Sifter for search & data extraction as a local process. You can also run both side by side in one mcpServers block.
Which MCP server should you choose?
Choose Fetch when
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: No auth required.
- You want tools like
create_entities, create_relations, add_observations.
Choose Sifter when
- You need dedicated capabilities in the Search & Data Extraction domain.
- You prefer a local stdio subprocess transport.
- Its auth model fits you: API key required.
- You have the keys it needs:
SIFTER_API_KEY, SIFTER_DEFAULT_API_KEY.
Feature & specification comparison
Rows where the two servers differ are marked.
| Spec | Sifter | |
|---|---|---|
| Category | Search & Data Extraction | Search & Data Extraction |
| Quality signal | 90/100 · Excellent | 55/100 · Good |
| Install command | Confirmed | Confirmed |
| Transport | Local subprocess (stdio) | Local subprocess (stdio) |
| Auth | No auth required | API key required |
| Pricing | Free | Freemium |
| Required env vars | None listed | SIFTER_API_KEYSIFTER_DEFAULT_API_KEY |
Tools & capabilities
Fetch tools 9
create_entitiesCreate multiple new entities in the knowledge graphcreate_relationsCreate multiple new relations between entities in the knowledge graph. Relations should be in active voiceadd_observationsAdd new observations to existing entities in the knowledge graphdelete_entitiesDelete multiple entities and their associated relations from the knowledge graphdelete_observationsDelete specific observations from entities in the knowledge graphdelete_relationsDelete multiple relations from the knowledge graphread_graphRead the entire knowledge graphsearch_nodesSearch for nodes in the knowledge graph based on a queryopen_nodesOpen specific nodes in the knowledge graph by their names
Sifter tools
No tool names declared yet. Check the project README from the listing page.
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.
Fetch
{
"mcpServers": {
"fetch": {
"command": "npx",
"args": [
"-y",
"@modelcontextprotocol/server-memory"
]
}
}
}
Sifter
{
"mcpServers": {
"sifter-ai-sifter": {
"command": "uvx",
"args": [
"sifter-mcp"
],
"env": {
"SIFTER_API_KEY": "YOUR_SIFTER_API_KEY_HERE",
"SIFTER_DEFAULT_API_KEY": "YOUR_SIFTER_DEFAULT_API_KEY_HERE"
}
}
}
}
Frequently asked questions
Fetch is categorized under Search & Data Extraction and uses a local stdio subprocess. Sifter belongs to Search & Data Extraction and uses a local stdio subprocess. Pick Fetch for search & data extraction work and Sifter for search & data extraction.
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.
Fetch is listed as free. Auth: no auth required. Sifter is listed as freemium — a free tier with paid plans. Auth: api key required. 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 fetch and sifter-ai-sifter as separate keys in the same mcpServers object, and your assistant will call tools from either one.
On AllMCPs, Fetch has a quality signal of 90/100 (Excellent) with 4 views, 0 installs and 91,147 GitHub stars. Sifter has 55/100 (Good) with 1 views, 0 installs and 54 GitHub stars.