Durchsuche wissenschaftliche Arbeiten mit Claude, Cursor oder jedem anderen MCP-kompatiblen KI-Tool.
BGPT ist ein entfernter Model Context Protocol (MCP) Server, der KI-Assistenten Zugriff auf eine Datenbank wissenschaftlicher Arbeiten bietet, die aus Volltextstudien erstellt wurde. Im Gegensatz zu typischen Suchwerkzeugen, die nur Titel und Zusammenfassungen liefern, extrahiert BGPT reine experimentelle Daten — Methoden, Ergebnisse, Schlussfolgerungen, Qualitätsbewertungen, Stichprobengrößen, Einschränkungen und über 25 Metadatenfelder pro Arbeit.
Füge BGPT zu deinem MCP-Client hinzu — für die kostenlose Stufe (50 kostenlose Ergebnisse) ist kein API-Schlüssel erforderlich.
Die meisten modernen MCP-Clients unterstützen direkte Remote-Verbindungen. BGPT bietet zwei Transportwege:
Transport | Endpunkt |
SSE |
|
Streamable HTTP |
|
Claude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}Cursor (.cursor/mcp.json):
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}Claude Code (CLI):
claude mcp add bgpt --transport sse https://bgpt.pro/mcp/sseCline / Roo Code / Windsurf — gleiche Konfiguration:
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}Tipp: Wenn dein Client Streamable HTTP unterstützt, kannst du stattdessen
https://bgpt.pro/mcp/streamverwenden.
{
"mcpServers": {
"bgpt": {
"command": "npx",
"args": ["-y", "bgpt-mcp"]
}
}
}npm install -g bgpt-mcpDann zur MCP-Konfiguration hinzufügen:
{
"mcpServers": {
"bgpt": {
"command": "bgpt-mcp"
}
}
}Verbinde dich mit einem der beiden Endpunkte:
SSE: https://bgpt.pro/mcp/sse
Streamable HTTP: https://bgpt.pro/mcp/streamDas ist alles. Kein Docker, kein Build-Schritt.
Related MCP server: mcp-spacefrontiers
BGPT bietet ein Werkzeug: search_papers
Parameter | Typ | Erforderlich | Beschreibung |
| string | Ja | Suchbegriffe (z. B. "CRISPR gene editing efficiency") |
| integer | Nein | Anzahl der zurückzugebenden Ergebnisse (1–100, Standard 10) |
| integer | Nein | Nur Arbeiten zurückgeben, die in den letzten N Tagen veröffentlicht wurden |
| string | Nein | Deine Stripe-Abonnement-ID für kostenpflichtigen Zugriff |
Jedes Ergebnis einer Arbeit enthält über 25 Felder, die aus dem Volltext extrahiert wurden:
Titel & DOI — Standard-Identifikatoren
Methoden — experimentelles Design, verwendete Techniken
Ergebnisse — reine Erkenntnisse, Messungen, statistische Ergebnisse
Schlussfolgerungen — was die Autoren festgestellt haben
Qualitätsbewertungen — Bewertung der methodischen Strenge
Stichprobengrößen — Anzahl der Teilnehmer/Proben
Einschränkungen — anerkannte Schwächen
Und mehr — Finanzierung, Interessenkonflikte, Studientyp usw.
Frage deinen KI-Assistenten:
"Suche nach aktuellen Arbeiten zu Ansprechraten bei der CAR-T-Zelltherapie"
BGPT liefert strukturierte experimentelle Daten, mit denen deine KI arbeiten kann — nicht nur eine Liste von Titeln.
Stufe | Kosten | Details |
Kostenlos | $0 | 50 kostenlose Ergebnisse, kein API-Schlüssel erforderlich |
Pay-as-you-go | $0.02/Ergebnis | Abrechnung pro zurückgegebenem Ergebnis. Erhalte einen API-Schlüssel unter bgpt.pro/mcp |
Your AI Assistant (Claude, Cursor, etc.)
│
│ MCP Protocol (SSE or Streamable HTTP)
▼
BGPT MCP Server
https://bgpt.pro/mcp/sse
https://bgpt.pro/mcp/stream
│
│ search_papers(query, ...)
▼
BGPT Paper Database
(full-text extracted data)
│
▼
Structured Results
(methods, results, quality scores, 25+ fields)BGPT ist ein gehosteter Remote-Server — dein MCP-Client verbindet sich über SSE oder Streamable HTTP. Keine lokale Installation erforderlich.
Literaturübersichten — Bitte deine KI, ein Thema mit echten experimentellen Daten zu untersuchen
Evidenzsynthese — Untermauere KI-Antworten mit tatsächlichen Studienergebnissen
Forschungsunterstützung — Finde Arbeiten nach Methodik, Ergebnis oder Aktualität
Faktencheck — Überprüfe Behauptungen anhand veröffentlichter experimenteller Ergebnisse
Antragstellung — Sammle schnell unterstützende Beweise für Vorschläge
Feld | Wert |
Protokoll | MCP (Model Context Protocol) |
Transport | SSE (Server-Sent Events) oder Streamable HTTP |
SSE-Endpunkt |
|
Streamable HTTP-Endpunkt |
|
Authentifizierung | Keine erforderlich (kostenlose Stufe) / Stripe API-Schlüssel (kostenpflichtig) |
{
"mcpServers": {
"bgpt": {
"url": "https://bgpt.pro/mcp/sse"
}
}
}Vollständige Dokumentation, FAQ und Einrichtungsanleitungen: bgpt.pro/mcp
E-Mail: contact@bgpt.pro
Probleme: GitHub Issues
API-Schlüssel / Abrechnung: bgpt.pro/mcp
Siehe CONTRIBUTING.md für Richtlinien zum Melden von Fehlern, Anfordern von Funktionen und Mitwirken.
Dieses Repository (Dokumentation, Beispiele und Konfigurationsdateien) ist unter der MIT-Lizenz lizenziert.
Der BGPT MCP API-Dienst selbst wird von BGPT betrieben und unterliegt seinen eigenen Nutzungsbedingungen.
Look up a single paper by its DOI.
| Name | Required | Description | Default |
|---|---|---|---|
| doi | Yes | The DOI of the paper (e.g. "10.1038/s41586-024-07386-0"). |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint and idempotentHint, indicating a safe, idempotent operation. The description adds no extra behavioral context (e.g., response format, authentication) beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single, direct sentence with no wasted words. It is front-loaded with the core action and resource.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one parameter and an output schema, the description fully covers the functionality. The output schema eliminates the need to describe return values.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage for the single 'doi' parameter, including an example. The description ('by its DOI') adds no additional meaning beyond what the schema already conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('look up') and the resource ('a single paper') using a specific identifier ('DOI'). This directly distinguishes it from the sibling tool 'search_papers', which would be used for broader searches.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance on when to use this tool versus alternatives. The sibling tool 'search_papers' is listed, but the description does not contrast or provide usage context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Search BGPT's database of scientific papers by keyword.
| Name | Required | Description | Default |
|---|---|---|---|
| query | Yes | Search terms (e.g. "CRISPR gene editing efficiency") Short, concise queries are best. English language only. Don't include years or filters — use the days_back and num_results params instead. | |
| days_back | No | Only return papers published within the last N days. | |
| num_results | No | Number of results to return (1-100, default 16). First 50 results are free, then billed at $0.01/result for paid users. |
| Name | Required | Description |
|---|---|---|
No output parameters | ||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint and idempotentHint. The description adds no behavioral context beyond 'search by keyword,' such as rate limits, pagination behavior, or billing details (which are in param descriptions but not the main description). Minimal additional value.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words. However, it is very brief and could be structured to front-load key information like what the tool does, but it does so adequately.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity, parameter richness, and presence of output schema, the description is sufficiently complete. It covers the core function and leaves return value details to the output schema.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema descriptions cover all parameters (100%). The description adds valuable usage hints beyond schema: 'Short, concise queries are best. English language only. Don't include years or filters...' This aids correct parameter use.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Description clearly states the verb (Search), resource (BGPT's database of scientific papers), and method (by keyword). It distinguishes from sibling lookup_paper which is likely a direct lookup by ID.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus lookup_paper. The description implies use for keyword search, but does not state when not to use it or provide alternatives. Usage is implied but not clearly delineated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The two tools have entirely distinct purposes: lookup_paper retrieves a specific paper by DOI, while search_papers finds papers by keyword. There is no overlap or ambiguity.
Both tool names follow a consistent verb_noun snake_case pattern (lookup_paper, search_papers), making them predictable and readable.
With only two tools, the server feels minimal but not unreasonable for a focused paper retrieval service. However, it's on the thin side for a database named BGPT.
The server provides basic search and retrieval by DOI, covering core read operations. Missing features like author-based search, citation info, or export are notable but not critical for simple use.
Search 8.5M scientific papers with LLM TLDRs, citations, linked entities, figures, and full text.
Science MCP — free science data APIs
Biomedical data: compounds, drug info, and molecular targets
Search 340M+ academic papers — citation graphs, semantic similarity, and AI literature reviews.
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