Evidence-based supplement recommendations, dosage guidance, form comparisons, and medication–nutrient interaction checks over MCP.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
The install command below started, but didn't respond the way we expected when we tried to talk to it.
npx -y supplement-advisor-mcpinitialize succeeded but no response to tools/list.
This is an experimental automated check and can have false negatives — missing environment variables, a slow cold install, etc. It doesn’t necessarily mean something’s wrong. Last checked 7d ago.
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by Supplement Advisor MCP.
recommend_supplementGet ranked supplement recommendations for a condition with clinical evidence, dosing, cost-per-dose, and purchase links
compare_formsCompare different forms of a supplement (e.g., magnesium glycinate vs citrate vs oxide) with absorption data and warnings
check_interactionsCheck if medications deplete nutrients — covers statins, metformin, PPIs, birth control, and more
get_dosageGet evidence-based dosage recommendations by condition, with clinical trial references and timing guidance
classify_formPaste any product name or ingredient list and get a quality verdict on the supplement form used
The supplement-advisor-mcp MCP server provides structured guidance for evaluating supplements, choosing between ingredient forms, checking medication-related nutrient depletion, and finding condition-specific dosage information. Its dataset covers 19 supplements, including magnesium glycinate, vitamin D3, omega-3, creatine, iron bisglycinate, vitamin B12, CoQ10, collagen, multivitamins, protein, biotin, calcium citrate, vitamin C, methylfolate, probiotics, ashwagandha, L-theanine, tongkat ali, and zinc.
The available guidance spans more than 40 conditions. Recommendations can include clinical evidence, dosage information, cost per effective daily dose, purchase links, timing guidance, warnings, and clinical trial references with PMIDs where available.
The server loads structured evidence data and makes it available through MCP tools. An AI assistant can select the tool that matches the user’s question and receive formatted, citation-backed results rather than relying only on general model knowledge.
Product rankings use cost per effective daily dose, third-party certification status, and clinical evidence. The README states that rankings are not based on sponsorship. Source material includes the NIH Dietary Supplement Label Database, PubMed, NSF International, and USP quality standards.
Run the supplement-advisor-mcp MCP server with npm’s package runner:
For Claude Desktop or Claude Code, add an MCP entry with npx as the command and -y plus supplement-advisor-mcp as the arguments. The project can also be built from source by cloning the repository, running npm install, executing npm run build, and starting it with npm start.
The README identifies Claude, Cursor, Windsurf, and other MCP-compatible clients as supported usage environments. No API key or other credential is specified in the supplied material.
recommend_supplement ranks supplements for a condition and can return evidence, dosing, cost per dose, and purchase links.compare_forms compares forms such as magnesium glycinate, citrate, and oxide using absorption information and warnings.check_interactions checks whether medications such as statins, metformin, proton-pump inhibitors, and birth control deplete nutrients.get_dosage provides condition-specific dosage recommendations, clinical trial references, and timing guidance.classify_form evaluates a pasted product name or ingredient list and returns a quality verdict for the supplement form.The supplement-advisor-mcp MCP server covers a defined supplement and condition dataset rather than an unrestricted catalog. Its interaction tool is described in terms of medication-related nutrient depletion, so the supplied documentation does not establish that it checks every type of drug interaction. Form classification is based on the supplied product name or ingredient list and focuses on the supplement form used.
The listed evidence sources and linked comparison pages provide provenance for the data, but the material does not specify update frequency, response schemas, operating-system requirements, or an external API configuration. The project is licensed under MIT.
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