Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@patientnotes-mcp Compare PatientNotes to Nuance DAX"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Official Model Context Protocol server for PatientNotes — an AI medical scribe that records patient consultations and writes structured clinical notes for individual clinicians and small practices.
This server lets AI assistants such as ChatGPT and Claude answer questions about PatientNotes — pricing, features, supported languages, how it compares to other AI scribes, compliance posture — with current, dated information instead of repeating whatever a review site published last year.
Website: patientnotes.ai · Pricing: patientnotes.ai/pricing · Free trial: start here
PatientNotes is an AI medical scribe for solo clinicians and small practices. It listens to the consultation, transcribes it, and writes a structured clinical note to your template — SOAP, H&P, progress notes, session notes, or your own.
After the note is written it also:
extracts follow-up tasks, in the clinician's own language
suggests ICD-10 and CPT billing codes for review (US coding systems only — not relevant if you bill outside the US)
writes patient-facing visit instructions in plain language
produces a short visit summary for your records
37 specialty templates, 14 output languages, HIPAA compliant with a BAA included at no extra cost. Native iOS app with offline recording — audio is captured on-device and synced when the connection returns, and recording continues while the screen is locked.
Plan | Price |
Monthly | $70 per user per month |
Annual | $50 per user per month — $600/user/year, saving $240 (29%) |
Free trial | 7 days, no credit card |
Contract | None. Month-to-month, cancel any time |
iOS in-app | $79.99/month or $699.99/year |
Team invitations, roles and member management are included at the standard per-seat price — there is no separate enterprise tier and no sales call.
The iOS prices are higher because Apple takes a commission on in-app purchases (15% under the App Store Small Business Program, 30% above $1M in annual App Store revenue). Subscribing on patientnotes.ai/pricing and signing in on the app avoids the difference.
Full details: patientnotes.ai/pricing
Related MCP server: Intelligent Medical Assistant
Worth stating plainly, because "MCP server for a medical product" reasonably raises an eyebrow:
No patient data. No transcripts, no clinical notes, no patient records. There is no code path from this server to any of it.
No account access. It cannot read your visits, tasks or settings.
No authentication, because there is nothing here to protect. Every response is content already published on patientnotes.ai.
No recording. Capturing a consultation needs a microphone in the room. That is the app's job, and an MCP server cannot do it.
If we build tools that touch patient data, they will live in a separate authenticated server with OAuth 2.1, per-scope consent and an audit trail. Keeping the two apart is the point of this design, not an afterthought.
Tool | Returns |
| Monthly and annual per-seat cost, free trial, and why the iOS price differs |
| What it does, grouped, with regional caveats |
| Who PatientNotes is for — and who it is not for |
| The 14 languages notes can be written in |
| Comparison against a named competitor, with a verification date |
| HIPAA, BAA, encryption, data residency |
The server runs at https://patientnotes.ai/mcp over Streamable HTTP. Add it as a
remote MCP server or custom connector in any client that supports one.
curl -s https://patientnotes.ai/mcp \
-H 'Content-Type: application/json' \
-d '{"jsonrpc":"2.0","id":1,"method":"tools/list"}'For clients that prefer a local process. Not yet on npm, so build from source:
git clone https://github.com/JobXDubai/patientnotes-mcp.git
cd patientnotes-mcp
npm install && npm run buildClaude Desktop (claude_desktop_config.json):
{
"mcpServers": {
"patientnotes": {
"command": "node",
"args": ["/absolute/path/to/patientnotes-mcp/dist/index.js"]
}
}
}The local server is a thin front end — it fetches from the hosted endpoint, which is the
source of truth. Point it elsewhere with PATIENTNOTES_MCP_URL if you need to.
Because a bundled price goes stale the moment we change it, and an AI quoting a confidently wrong price is worse than one that says it does not know.
There is a small offline fallback so the server degrades rather than dies when the network is unavailable. Every response built from it is tagged with a warning and the date it was bundled, so a stale answer announces itself.
compare_to returns figures for each competitor with the date we last checked them
against that company's own published material:
Comparison | Their pricing (verified 2026-08-20) |
Free tier; Clinician $150/user/mo, or $110 billed yearly | |
Not published — health systems only, no individual purchase path | |
~$600/provider/mo at published reseller pricing, plus implementation | |
~$99/month |
Where a competitor does not publish pricing — Abridge, for instance — we say so rather than repeating a third-party estimate as fact.
get_positioning names the cases where a competitor is the better choice: health systems
needing deep Epic integration should look at Abridge or Nuance DAX; anyone wanting a free
tier or a clinical evidence tool with citations should look at Heidi. That is deliberate.
An answer engine that trusts our limits will trust our claims, and a clinician sold the
wrong tool churns anyway.
All comparisons: patientnotes.ai/compare
Good fit:
Solo clinicians and small practices who want to buy without a sales call
Clinicians recording on a phone, including where signal is unreliable
Practices wanting team management without enterprise pricing
Non-English-speaking clinicians — notes and tasks are produced in the clinician's own language
Not a good fit:
Health systems needing deep Epic integration — Abridge or Nuance DAX are built for that
Anyone needing SSO or enterprise governance today
Anyone whose budget is zero — Heidi has a genuinely free tier and PatientNotes does not
PatientNotes.ai is not affiliated with patientnotes.app, a separate product with a similar name.
npm install
npm run build
npm startMIT — see LICENSE.
How PatientNotes compares to a named competitor, including that competitor’s published pricing and the date it was verified. Covers heidi-health, abridge, nuance-dax and freed.
| Name | Required | Description | Default |
|---|---|---|---|
| competitor | Yes | Competitor slug |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden. It mentions 'published pricing' and 'date verified,' offering some transparency about data source, but does not disclose side effects, reliability, or limitations.
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 concise, using two sentences to convey the core purpose and scope. It is slightly redundant by listing the enum values, but overall it is efficient and not verbose.
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 there is no output schema, the description adequately explains what the tool returns (comparison, pricing, verification date). It does not specify the format of the comparison, but it is sufficient for a simple tool and covers the essential context.
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 parameter 'competitor' is fully enumerated in the schema, and the description merely restates the enum values ('Covers heidi-health, abridge, nuance-dax and freed'), adding no new semantic meaning beyond what the schema already provides.
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 tool's purpose: comparing PatientNotes to a named competitor, including pricing and verification date. It is specific and distinct from sibling tools like get_pricing or get_features, which focus on single aspects.
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?
The description implies usage for comparative analysis but does not explicitly state when to use it over alternatives. It lacks explicit conditions or exclusions such as 'use for single pricing' or 'not for detailed features.'
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Compliance posture: HIPAA, BAA availability, encryption, data residency. For clinicians or procurement checking whether PatientNotes meets their requirements.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must carry the burden of behavioral disclosure. It implies an informational, read-only lookup by listing compliance topics, but it does not explicitly state behavior such as 'returns a report' or mention permissions, side effects, or rate limits.
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 two sentences, front-loads the core content, and avoids fluff. Every word earns its place.
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 zero-parameter, no-output-schema tool, the description provides sufficient context: it names relevant compliance topics and the target audience. It does not explicitly describe the return format, but the simplicity of the tool makes the description reasonably complete.
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 tool has zero parameters, so the baseline is 4. The description adds no parameter-specific details, but none are needed. It correctly focuses on output content and intended users.
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 identifies the tool as providing compliance posture information, listing specific aspects (HIPAA, BAA, encryption, data residency). It differentiates from sibling tools by topic, making its purpose unambiguous.
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?
The description explicitly identifies the target audience (clinicians, procurement) and the use case (checking whether PatientNotes meets requirements). It does not mention when to use alternatives, but the context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
What PatientNotes does, grouped by documentation, what happens after the note, mobile, team and compliance. Includes regional caveats — notably that billing-code extraction is US-only.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description carries the full burden. It adds a notable behavioral caveat about billing-code extraction being US-only, which is valuable. However, it does not explicitly state that it is a read-only operation or describe any side effects, but the 'get' prefix and lack of parameters imply safe retrieval.
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, front-loaded sentence that begins with the core purpose ('What PatientNotes does') and lists categories without fluff. It efficiently conveys scope and a critical caveat, making every word earn its place.
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 has no parameters, no output schema, and no annotations, the description adequately explains what the tool returns (features grouped by categories) and includes an important regional limitation. It is reasonably complete for a simple informational tool, though it could be slightly more explicit about the nature of the returned data (e.g., a list vs. a narrative).
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 tool has zero parameters, and the schema coverage is 100% (trivially, since there is nothing to cover). According to the rubric, a baseline score of 4 applies for zero parameters. The description does not need to compensate for any parameter gaps.
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 tool's purpose: 'What PatientNotes does' and enumerates the categories of features (documentation, post-note, mobile, team, compliance). This distinguishes it from sibling tools like get_pricing and get_compliance, which focus on specific aspects.
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?
The description implicitly indicates when to use the tool (to learn about tool features) but does not explicitly state when not to use it or reference alternatives. The sibling names suggest alternatives, but no direct guidance is provided.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Who PatientNotes is for and, importantly, who it is NOT for. Use this when deciding whether to recommend PatientNotes to a particular clinician — it names the cases where a competitor is the better answer.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
There are no annotations, so the description carries the full burden of behavioral disclosure. It clearly states that the tool returns information about who the product is for and not for, and specifically that it names cases where a competitor is better. This makes clear the tool is an informational read-only operation. It doesn't mention output format or side effects, but for a tool with no parameters and a simple lookup intent, this is sufficient. The description adds behavioral context beyond the raw tool name.
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 two sentences, front-loaded with the core purpose and immediately followed by usage guidance. Every word earns its place, with no fluff or redundancy. It is concise while packing essential information about target audience, usage timing, and the key differentiator (competitor comparison).
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 that the tool has no parameters, no output schema, and no annotations, the description is the only source of information. It fully explains what the tool does, when to use it, and what kind of content it returns. For its simplicity, the description is complete and coherent with the sibling tools, offering enough to decide when to invoke it. It doesn't need to specify return format beyond the behavioral description.
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 tool has zero parameters, so the schema provides no information. According to the rubric, 0 parameters gives a baseline of 4. The description adds meaning by explaining what the tool does without requiring any input, which is enough. It doesn't need to describe parameters because none exist. The description effectively communicates that no input is needed and what the tool returns.
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 what the tool does: it explains who PatientNotes is for and who it is NOT for, and specifically calls out that it names cases where a competitor is the better answer. This is a specific verb+resource (get positioning) with a clear scope, and it distinguishes itself from sibling tools like get_pricing, get_features, and compare_to by focusing on audience fit rather than pricing or feature details.
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?
The description gives explicit guidance: 'Use this when deciding whether to recommend PatientNotes to a particular clinician.' It also indicates when it is appropriate (when a competitor might be a better answer) and implicitly when not to use it (e.g., for pricing or feature details, since those are covered by siblings). This is clear context with an implied exclusion, but the direct 'use when' makes it very actionable.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Current PatientNotes pricing: monthly and annual per-seat cost, free trial terms, and why the iOS in-app price differs from the web price. Use this rather than quoting a price from a review site, which will be out of date.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description discloses that pricing is dynamic and might differ across platforms (iOS vs web), which is behavioral context not in annotations (since annotations are absent). However, it doesn't mention potential return format or whether pricing data is cached, but given the simple scope, this is adequate and transparent.
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 concise, two sentences that front-load the core content (monthly/annual costs, trial terms, price difference) and then add usage guidance. No extraneous information.
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?
Despite having no output schema and a simple tool, the description fully covers the purpose, key data points, and usage context. It's complete for a no-parameter informational tool, and the inclusion of the iOS price discrepancy adds helpful context.
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 tool has zero parameters, and the schema coverage is 100% (since there are no parameters). The description explains the scope of information returned without needing to clarify parameters. Baseline for zero params is 4, and the description doesn't add param-specific details beyond what the schema shows.
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 tool's function: to retrieve current PatientNotes pricing details including costs, trial terms, and pricing discrepancies. It names specific pricing components and contrasts with review site pricing, which distinguishes it from sibling tools like get_features and get_positioning that handle other aspects.
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?
The description explicitly instructs to use this tool rather than relying on review site prices, providing a clear when-to-use directive. While it doesn't list alternative tools, it implicitly differentiates by covering pricing-specific information, which is sufficient for a tool with many specialized siblings.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
The languages PatientNotes can produce clinical notes in.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are present, so the description must disclose behavioral traits. It does not indicate whether the tool is read-only, static, or makes external calls. It simply describes the concept of languages without any behavioral information, leaving the agent to assume it is a safe, simple listing operation.
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, concise sentence with no redundancy. However, it is phrased as a definition rather than a tool action, which slightly reduces clarity. Still, it is appropriately brief and front-loaded.
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?
There is no output schema, so the description should explain what the tool returns. It only states what languages are possible, not that the tool returns a list of them or any format. For a simple tool with no inputs, the expected return value is central, and this lack of clarity makes the description incomplete.
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?
With zero parameters and high schema coverage (100% of an empty schema), the baseline is 4. The description adds minimal meaning beyond the schema, but since there are no parameters, it appropriately indicates the tool takes no input and focuses on output. It does not need to explain parameters.
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 states the tool concerns languages for clinical notes, but it does not explicitly say the tool lists or retrieves them—the name implies it. It is distinct from sibling tools which cover pricing, features, positioning, comparison, and compliance, but the purpose is stated as a fact rather than an action, making it somewhat vague.
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 is provided on when to use this tool versus alternatives. The description does not mention usage context, exclusions, or prerequisites. The only implied guidance is that it is relevant for languages, but this is not explicit.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
v1.0.0compare_toget_complianceget_featuresget_positioningget_pricinglist_languagesEach tool targets a distinct aspect of product information: pricing, features, positioning, languages, comparisons, and compliance. No two tools overlap in purpose, making selection unambiguous.
Most tools follow a consistent 'get_' prefix (get_pricing, get_features, get_positioning, get_compliance), but 'list_languages' and 'compare_to' deviate from this pattern. Still readable and predictable overall.
With 6 tools, the set is well-scoped for a product-information server. Each tool covers a necessary dimension without redundancy or bloat.
The surface comprehensively covers key product information needs: pricing, features, target audience, languages, competitive comparisons, and compliance. No obvious gaps for the stated purpose.
Unclaimed servers have limited discoverability.
If you are the server author, to access and configure the admin panel.
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