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Quickstart
Install Scholar, connect your agent and run a first search in a few minutes. No account or API key needed.
# Quickstart Scholar is a local MCP server that runs on the same computer as your agent. This page uses Claude Code as the example. Other clients follow the same steps, and [Install in your client](/scholar-mcp/clients/) has their configuration. This guide installs Scholar MCP 0.9.0 from PyPI, including the CLI and scientific data tools. Plugins, containers and desktop bundles use the same release. The compatibility wheel index supplies native dependencies for Intel macOS and Windows on ARM. <Steps> 1. ## Install uv Scholar runs through [uv](https://docs.astral.sh/uv/), which prepares a separate Python 3.12 for it. If `uv --version` already works, skip this step. <Tabs syncKey="os"> <TabItem label="macOS and Linux"> ```bash curl -LsSf https://astral.sh/uv/install.sh | sh ``` </TabItem> <TabItem label="Windows"> ```powershell powershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" ``` </TabItem> </Tabs> 2. ## Connect your agent <Tabs syncKey="install"> <TabItem label="Scholar CLI"> Install the `scholar-mcp` command, then let it write the client configuration. ```bash uv tool install --python 3.12 \ --find-links https://github.com/Liyux3/scholar-mcp/releases/download/v0.9.0/wheel-index.html \ "scholar-mcp[rerank]==0.9.0" scholar-mcp install claude-code ``` `install` backs up a file before changing it and can be run again safely. `--all` configures every client it detects, `--dry-run` only shows the change, and `--profile research` adds the citation graph and paper library. `scholar-mcp update` upgrades the installed command. For a client pinned to a uvx version, rerun the installer with the new release. </TabItem> <TabItem label="Manual"> To skip installing the command, register the server with uvx. On first launch uvx prepares Python 3.12 and the local ranking model. ```bash claude mcp add scholar -- uvx --python 3.12 \ --find-links https://github.com/Liyux3/scholar-mcp/releases/download/v0.9.0/wheel-index.html \ --from 'scholar-mcp[rerank]==0.9.0' scholar-mcp ``` This registers the six core tools for the current project. `--scope user` makes it apply to every project, and `-e SCHOLAR_MCP_EXTENSIONS=research` before `--` adds the citation graph and paper library. </TabItem> <TabItem label="Ask your agent"> Works in any client, including ones not listed anywhere on this site. Paste this into your agent: ```text Install Scholar MCP into the client you are running in, following https://raw.githubusercontent.com/Liyux3/scholar-mcp/v0.9.0/llms-install.md Then tell me to restart, and check that search_papers is available. ``` The guide tells the agent which command to start and how common clients write it down, so the agent works out its own client's format. </TabItem> </Tabs> 3. ## Check the connection Start a new Claude Code session and run `/mcp`. `scholar` should show as connected. In a terminal, `scholar-mcp doctor` shows the version, the registered clients, and which sources and ranking model are available. 4. ## Ask a research question Ask the way you would ask a colleague. The agent chooses the tools itself. ```text Find recent work on evaluating long-term memory in LLM agents, read the most cited one and compare its benchmarks. ``` The agent searches with `search_papers`, opens the chosen paper with `read_paper` and answers from the text. Follow up with *who cites this?* or *save these three to the memory collection*. 5. ## Add API keys when needed Every key is optional. Keys widen coverage and raise limits. Save each one once with `scholar-mcp keys set NAME` and every client uses it, or put them in the `env` block of one client's configuration. ```json title="Server environment" "env": { "S2_API_KEY": "your-semantic-scholar-key", "OPENALEX_API_KEY": "your-openalex-key", "DASHSCOPE_API_KEY": "your-dashscope-key" } ``` If you add only two, make them the free ones that lift the tightest limits: an OpenAlex key (without one OpenAlex allows about a hundred searches a day) and a registered OpenAIRE service, `OPENAIRE_CLIENT_ID` and `OPENAIRE_CLIENT_SECRET` (60 requests an hour without it, 7,200 with it). A Semantic Scholar key raises its limits and enables snippet search and recommendations. An OpenAlex key is used for its keyword search, semantic search and citation data. A DashScope key moves ranking to the cloud Qwen3 reranker. All variables are in [Configuration](/scholar-mcp/configuration/). </Steps> <Aside type="tip" title="Research profile"> The core profile has six tools. Literature reviews usually also want `build_paper_graph` and `paper_library`. Add `--profile research` when installing, or set `SCHOLAR_MCP_EXTENSIONS=research`. The Claude Code and Codex plugins enable it by default and include the Deep Research skill. </Aside> ## Next steps <div class="sc-cards-2"> <LinkCard title="Research workflows" description="Search, screen, read and save, quickly and well." href="/scholar-mcp/research-workflows/" /> <LinkCard title="Command line" description="Every tool in the terminal, plus install, doctor and update." href="/scholar-mcp/cli/" /> </div>Scholar is a local MCP server that runs on the same computer as your agent. This page uses Claude Code as the example. Other clients follow the same steps, and Install in your client has their configuration.
This guide installs Scholar MCP 0.9.0 from PyPI, including the CLI and scientific data tools. Plugins, containers and desktop bundles use the same release. The compatibility wheel index supplies native dependencies for Intel macOS and Windows on ARM.
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Install uv
Section titled “Install uv”Scholar runs through uv, which prepares a separate Python 3.12 for it. If
uv --versionalready works, skip this step.curl -LsSf https://astral.sh/uv/install.sh | shpowershell -ExecutionPolicy ByPass -c "irm https://astral.sh/uv/install.ps1 | iex" -
Connect your agent
Section titled “Connect your agent”Install the
scholar-mcpcommand, then let it write the client configuration.uv tool install --python 3.12 \--find-links https://github.com/Liyux3/scholar-mcp/releases/download/v0.9.0/wheel-index.html \"scholar-mcp[rerank]==0.9.0"scholar-mcp install claude-codeinstallbacks up a file before changing it and can be run again safely.--allconfigures every client it detects,--dry-runonly shows the change, and--profile researchadds the citation graph and paper library.scholar-mcp updateupgrades the installed command. For a client pinned to a uvx version, rerun the installer with the new release.To skip installing the command, register the server with uvx. On first launch uvx prepares Python 3.12 and the local ranking model.
claude mcp add scholar -- uvx --python 3.12 \--find-links https://github.com/Liyux3/scholar-mcp/releases/download/v0.9.0/wheel-index.html \--from 'scholar-mcp[rerank]==0.9.0' scholar-mcpThis registers the six core tools for the current project.
--scope usermakes it apply to every project, and-e SCHOLAR_MCP_EXTENSIONS=researchbefore--adds the citation graph and paper library.Works in any client, including ones not listed anywhere on this site. Paste this into your agent:
Install Scholar MCP into the client you are running in, followinghttps://raw.githubusercontent.com/Liyux3/scholar-mcp/v0.9.0/llms-install.mdThen tell me to restart, and check that search_papers is available.The guide tells the agent which command to start and how common clients write it down, so the agent works out its own client’s format.
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Check the connection
Section titled “Check the connection”Start a new Claude Code session and run
/mcp.scholarshould show as connected. In a terminal,scholar-mcp doctorshows the version, the registered clients, and which sources and ranking model are available. -
Ask a research question
Section titled “Ask a research question”Ask the way you would ask a colleague. The agent chooses the tools itself.
Find recent work on evaluating long-term memory in LLM agents,read the most cited one and compare its benchmarks.The agent searches with
search_papers, opens the chosen paper withread_paperand answers from the text. Follow up with who cites this? or save these three to the memory collection. -
Add API keys when needed
Section titled “Add API keys when needed”Every key is optional. Keys widen coverage and raise limits. Save each one once with
scholar-mcp keys set NAMEand every client uses it, or put them in theenvblock of one client’s configuration.Server environment "env": {"S2_API_KEY": "your-semantic-scholar-key","OPENALEX_API_KEY": "your-openalex-key","DASHSCOPE_API_KEY": "your-dashscope-key"}If you add only two, make them the free ones that lift the tightest limits: an OpenAlex key (without one OpenAlex allows about a hundred searches a day) and a registered OpenAIRE service,
OPENAIRE_CLIENT_IDandOPENAIRE_CLIENT_SECRET(60 requests an hour without it, 7,200 with it). A Semantic Scholar key raises its limits and enables snippet search and recommendations. An OpenAlex key is used for its keyword search, semantic search and citation data. A DashScope key moves ranking to the cloud Qwen3 reranker. All variables are in Configuration.