# PubMed Central MCP > PubMed Central MCP connects your AI agent directly to PMC, the world's open-access library of biomedical and life sciences literature. Search millions of full-text articles, analyze citation networks, and pull structured data in JSON format without ever leaving your client. This is deep research retrieval for modern science. ## Overview - **Category:** knowledge-management - **Price:** Free - **Tags:** pubmed, biomedical, open-access, academic-search, full-text ## Description When you need to understand a complex scientific topic, you shouldn't have to manually download PDFs and cross-reference identifiers. Your AI client connects directly to PubMed Central through this MCP, giving you immediate access to millions of open-access articles. You can ask your agent to find all studies that mention a specific gene, then pull the full text for three of them in structured JSON format. The system handles complex data mapping, automatically converting between identifiers like PMCID, PMID, and DOI so everything lines up perfectly. Whether you're tracking how much one paper influenced subsequent research by finding articles that cite it, or just needing a summary of key metadata from an open-access record, this MCP makes the entire process conversational. Because we host over 4,000 tools in our catalog, Vinkius ensures your agent can access PMC alongside everything else you need for serious academic work. ## Tools ### get_bioc_article Retrieves a complete scientific paper's content in structured JSON or XML format via the BioC API. ### get_citing_articles Identifies and lists PMC articles that reference a specific PubMed ID, mapping its academic impact. ### convert_ids Converts article identifiers between PMCID, PMID, and DOI formats to ensure data consistency across sources. ### get_oa_record Finds crucial information like citation details, licensing terms, and file locations for open-access articles. ### oai_pmh_request Harvests structured metadata from the PMC OAI-PMH Service for batch data collection. ### search_articles Searches PubMed Central using complex queries involving keywords, authors, and date ranges to locate articles. ### get_article_summary Pulls brief metadata summaries for PMC articles, giving you key details without needing the full text. ## Prompt Examples **Prompt:** ``` Search PubMed Central for recent articles about 'CRISPR gene editing' published in 2023. ``` **Response:** ``` I found several articles. Notable ones include PMC1012345 ('Advances in CRISPR...') and PMC1023456. Would you like a summary of the most relevant one? ``` **Prompt:** ``` Get the full-text content of article PMC7840891 in JSON format. ``` **Response:** ``` I've retrieved the BioC JSON for PMC7840891. It contains sections for Introduction, Methods, Results, and Discussion. Which part should I analyze first? ``` **Prompt:** ``` Convert the DOI 10.1038/s41586-020-2012-7 to a PMCID. ``` **Response:** ``` The DOI 10.1038/s41586-020-2012-7 maps to PMCID: PMC7095063 (and PMID: 32015508). ``` ## Capabilities ### Find and filter literature Search the entire archive using advanced criteria like author name, publication date, or specific keywords. ### Extract full-text content Retrieve the complete article text in structured JSON or XML format for immediate data analysis. ### Map scientific identifiers Convert between different types of academic IDs (PMCID, PMID, DOI) to keep your research sources consistent. ### Analyze citation impact Track the influence of a specific paper by finding all subsequent articles that cite it. ### Gather article summaries and details Pull metadata, license information, or simple abstracts for multiple open-access records quickly. ## Use Cases ### Mapping a literature gap A researcher needs to prove that no one has studied the interaction between Protein A and Gene B in mammals. They use search_articles to find all relevant papers, then they run get_citing_articles on key publications to ensure every potential connection has been documented. ### Processing a cohort dataset A data scientist needs the full text and license information for 50 specific open-access articles. They use oai_pmh_request or get_oa_record to harvest all required metadata before using get_bioc_article on each one. ### Fact-checking clinical claims A medical professional needs instant verification of a drug's efficacy. They ask their agent to find articles about the drug and then use get_article_summary to pull quick, reliable metadata on the most recent clinical trials. ### Building a structured knowledge graph A bioinformatics team needs to build a database of relationships between genes. They run search_articles for gene pairs and then use get_bioc_article to extract the specific data points from the full text, making it machine-readable. ## Benefits - Stop copying and pasting identifiers. Use convert_ids to instantly map PMCID, PMID, and DOI across your entire project dataset, keeping everything clean for analysis. - Ditch manual PDF downloading. With get_bioc_article, you pull the full text of an article directly into a structured JSON format that your agent can read, analyze, and summarize immediately. - Track academic influence effortlessly. Instead of guessing impact, use get_citing_articles to automatically find all the papers that built on a specific study, giving you a clear picture of its reach. - Gather massive metadata sets in bulk. Use oai_pmh_request or get_oa_record to harvest licensing info and file locations for dozens of open-access records simultaneously. - Cut down research time instantly. Instead of reading abstracts one by one, use search_articles to filter millions of papers based on precise criteria like 'gene X' published after 2020. ## How It Works The bottom line is that you get organized, deep scientific knowledge delivered through plain conversation, bypassing manual database work entirely. 1. Subscribe to the MCP within Vinkius and provide your NCBI Tool Name and email address. 2. Your agent authenticates with the service, making sure all credentials are linked for high-volume querying. 3. You ask your AI client a question—like 'Find me articles citing X'—and the system returns structured data directly into your workspace. ## Frequently Asked Questions **How do I find all the papers related to a specific study using PubMed Central MCP?** You run the get_citing_articles tool. This finds articles that reference a given PMID, letting you track the scientific impact and lineage of research. **Does PubMed Central MCP only handle one type of identifier?** No. The convert_ids tool lets you reliably switch between PMCID, PMID, and DOI formats, keeping your data consistent no matter where the source ID came from. **Can I get the full text in JSON format using PubMed Central MCP?** Yes. You use get_bioc_article to retrieve the complete article content structured as BioC XML or JSON, making it immediately usable for analysis. **What is the best way to collect metadata from multiple open-access articles?** You can combine search_articles with get_oa_record. First find the list of article IDs, then run get_oa_record on those IDs to gather citation data and license info in bulk. **Is oai_pmh_request better than getting a summary?** They serve different purposes. Use get_article_summary for a quick, simple abstract. Use oai_pmh_request if you need to programmatically harvest large batches of structured metadata.