| 1 |
| Ecosystem | 0 | 0 |
| Match Graph | 0 | 0 |
| Pricing | Free | Free |
| Starting Price | — | $10/mo |
| Capabilities | 10 decomposed | 13 decomposed |
| Times Matched | 0 | 0 |
Defines a strictly-typed TypeScript configuration layer (src/config/) that serves as a single source of truth for identity and access control across GitHub, Google Workspace, and Discord. The configuration uses a declarative model where members, roles, and repository access levels are expressed as TypeScript objects, which are then validated for schema correctness and referential integrity before being transformed into platform-specific resources via Pulumi providers. This approach enables peer review of all access changes through Pull Requests and prevents configuration drift across multiple platforms.
Unique: Uses a strictly-typed TypeScript configuration layer (src/config/) with compile-time type safety and referential integrity validation, rather than YAML or JSON-based IaC that relies on runtime validation. The configuration is transformed into platform-specific resources through Pulumi providers, enabling a unified abstraction over heterogeneous platforms (GitHub, Google Workspace, Discord).
vs alternatives: Provides stronger type safety and IDE support than YAML-based IaC tools like Terraform or CloudFormation, while maintaining the auditability and peer-review benefits of infrastructure-as-code through Git-based workflows.
Automatically provisions and synchronizes GitHub teams and repository permissions by translating declarative configuration into github.Team and github.TeamMembership Pulumi resources. The system reads member and role definitions from the configuration layer, maps them to GitHub team structures, and uses the GitHub Pulumi provider to create/update teams, manage memberships, and enforce repository access levels. Changes are previewed via pulumi preview before being applied, enabling safe deployments with rollback capability.
Unique: Uses Pulumi's GitHub provider to manage teams and memberships as first-class infrastructure resources with state tracking and preview capabilities, rather than shell scripts or GitHub CLI commands. This enables safe, auditable deployments with automatic rollback on failure and full Git-based change history.
vs alternatives: Provides safer deployments than GitHub CLI scripts because Pulumi tracks state and can detect drift, while offering better auditability than manual GitHub UI changes through declarative configuration and Git history.
Automatically provisions @modelcontextprotocol.io email accounts and manages Google Workspace groups by translating configuration into googleworkspace.User and googleworkspace.Group Pulumi resources. The system reads member definitions with Google Workspace prefixes from configuration, creates user accounts with standardized email addresses, and manages group memberships. Validation ensures that Google Workspace prefixes are globally unique across the configuration to prevent email conflicts. The Pulumi provider handles API interactions with Google Workspace, including account creation, group assignment, and lifecycle management.
Unique: Enforces Google Workspace prefix uniqueness through configuration-time validation (scripts/validate-config.ts) before provisioning, preventing email conflicts at the source rather than handling them reactively. Uses Pulumi's Google Workspace provider to manage user and group resources with state tracking, enabling safe deployments and drift detection.
vs alternatives: Provides stronger validation and conflict prevention than manual Google Workspace admin console management, while offering better auditability than shell scripts through Pulumi's state tracking and declarative configuration.
Automatically synchronizes Discord server roles with organizational membership by translating role definitions into Discord role assignments via Pulumi. The system reads member and role definitions from configuration, maps them to Discord roles, and uses the Discord Pulumi provider to assign/revoke roles. This ensures that Discord server roles remain aligned with the authoritative organizational structure defined in configuration, preventing manual role management drift.
Unique: Treats Discord role assignments as infrastructure resources managed through Pulumi, enabling state tracking and drift detection rather than one-off bot commands. This approach ensures that Discord roles remain synchronized with the authoritative configuration even if manual changes are made in the Discord UI.
vs alternatives: Provides better auditability and synchronization guarantees than Discord bots that only respond to commands, while maintaining the flexibility of Pulumi's infrastructure-as-code approach.
Validates all configuration changes before deployment by running a suite of validation scripts (scripts/validate-config.ts) that enforce schema correctness, referential integrity, and business rules. The validation layer checks that all member IDs exist, roles are correctly assigned, Google Workspace prefixes are globally unique, and repository access configurations reference valid teams and repositories. Validation runs automatically in CI/CD (GitHub Actions) on Pull Requests, preventing invalid configurations from being merged. The system uses TypeScript's strict type system to catch errors at compile time, supplemented by runtime validation for cross-entity constraints.
Unique: Combines compile-time TypeScript type checking with runtime validation scripts that enforce cross-entity constraints (e.g., Google Workspace prefix uniqueness, member ID existence). This two-layer approach catches both structural errors and business logic violations before deployment.
vs alternatives: Provides stronger validation than JSON Schema alone because TypeScript's type system catches structural errors at compile time, while runtime scripts enforce domain-specific rules that would require custom JSON Schema extensions.
Manages Pulumi infrastructure state using a Google Cloud Storage (GCS) backend instead of local state files, enabling safe multi-user deployments and state recovery. The Pulumi project is configured (Pulumi.yaml) to use a GCS bucket as the remote state backend, which stores the current state of all provisioned resources (GitHub teams, Google Workspace users, Discord roles). This enables multiple team members to deploy changes safely without state conflicts, provides automatic backups, and allows state inspection and recovery if deployments fail. The GCS backend is authenticated via Google Cloud SDK credentials.
Unique: Uses GCS as a remote state backend rather than local files or Pulumi's managed service, providing organization-specific control over state storage and backup policies. This approach is particularly suitable for open-source communities that want to avoid vendor lock-in while maintaining safe multi-user deployments.
vs alternatives: Provides better multi-user safety than local Pulumi state files (which can cause conflicts), while offering more control than Pulumi's managed backend service (which stores state in Pulumi's infrastructure).
Automatically deploys infrastructure changes to GitHub, Google Workspace, and Discord when configuration is merged to the main branch using GitHub Actions workflows. The CI/CD pipeline (defined in .github/workflows/) runs pulumi up on the main branch, which applies all pending infrastructure changes. Pull Requests trigger pulumi preview to show what changes will be deployed, enabling reviewers to understand the impact before approving. The workflow is authenticated via GitHub secrets containing Pulumi credentials, Google Cloud credentials, and platform-specific API tokens, ensuring secure credential management without exposing secrets in the repository.
Unique: Integrates Pulumi deployments directly into GitHub Actions workflows, enabling preview-on-PR and automatic-on-merge patterns without requiring external CI/CD systems. This approach leverages GitHub's native workflow system and secret management, reducing operational overhead.
vs alternatives: Simpler to set up than external CI/CD systems (Jenkins, GitLab CI) because it uses GitHub's native Actions, while providing better auditability than manual Pulumi CLI deployments through workflow logs and Git history.
Maintains a centralized member registry and role definitions that serve as the authoritative source for all identity and access decisions across platforms. The member registry (src/config/members.ts) defines individual members with platform-specific identifiers (GitHub username, Google Workspace prefix, Discord user ID), while role definitions (src/config/roles.ts) map abstract roles (e.g., 'maintainer', 'contributor') to platform-specific team/group assignments. This separation enables role-based access control where members are assigned to roles, and roles are automatically translated into platform-specific permissions. The system uses TypeScript types to ensure that all member references are valid and all role assignments are correctly structured.
Unique: Uses TypeScript's type system to enforce that all member references are valid and all role assignments reference existing members and roles, catching errors at compile time rather than runtime. This approach provides stronger guarantees than JSON-based member registries that rely on runtime validation.
vs alternatives: Provides better type safety and IDE support than JSON-based member registries, while maintaining the simplicity of a declarative configuration approach compared to external identity providers (Okta, Azure AD).
+2 more capabilities
Generates single-line and multi-line code suggestions in real-time as developers type, using semantic indexing of the entire codebase to retrieve relevant type definitions, function signatures, and contextual patterns. The system maintains a 1M token context window (Pro/Team tiers) that enables suggestions informed by distant code definitions and cross-file dependencies, constructed via local codebase semantic search rather than simple token-based recency. Suggestions adapt to detected coding style on Pro/Team tiers through implicit pattern learning from recent edits.
Unique: 1M token context window with codebase-wide semantic indexing enables suggestions informed by distant code definitions and cross-file patterns, versus competitors (Copilot, Tabnine) that typically use fixed context windows (4K-32K tokens) or file-local context. Claimed 250ms latency suggests optimized retrieval pipeline, though indexing mechanism and performance at scale remain undisclosed.
vs alternatives: Larger context window than GitHub Copilot (8K-32K tokens) and faster latency than unnamed competitors (250ms vs 783ms claimed), enabling suggestions on large codebases with minimal typing delay; trade-off is cloud dependency and undisclosed free tier limitations.
Provides a separate chat interface supporting multiple LLM backends (GPT-4o, Claude 3.5 Sonnet, GPT-4, others) for conversational code assistance. Users attach files, reference recent edits, and trigger compiler diagnostic uploads; the system generates diffs and applies code changes directly to the editor. Model selection is per-conversation, and $5/month in credits (included in Pro/Team) covers external model API costs; overage pricing is undisclosed. Hotkey-driven workflow enables rapid context switching between inline completion and chat.
Unique: Multi-model chat interface with per-conversation model selection and integrated diff application, combined with compiler diagnostic auto-upload. Unlike Copilot Chat (single model per tier) or standalone ChatGPT, Supermaven Chat unifies multiple LLM backends in a single hotkey-driven workflow with direct editor integration for change application.
Supermaven scores higher at 71/100 vs access at 24/100. access leads on ecosystem, while Supermaven is stronger on adoption and quality.
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vs alternatives: Supports multiple LLM backends (GPT-4o, Claude 3.5 Sonnet) in one interface with included credits, whereas GitHub Copilot Chat is single-model per tier and requires separate ChatGPT subscription for model switching; trade-off is credit limits and unknown overage pricing.
Supermaven Chat can automatically upload compiler diagnostic messages (errors, warnings) alongside code context to provide error-aware suggestions and fixes. The mechanism is described as 'automatically uploading your code together with compiler diagnostic messages,' but specific language/compiler support and the upload trigger mechanism are undisclosed. This feature is Chat-only and not available in inline completion.
Unique: Automatic compiler diagnostic upload in Chat for error-aware suggestions, versus competitors (Copilot, Tabnine) that require manual error context or have limited diagnostic integration. Supermaven's approach reduces friction but with undisclosed language/compiler support.
vs alternatives: Automatic diagnostic upload reduces manual context-gathering compared to manual copy-paste; trade-off is undisclosed language support and unclear upload trigger mechanism.
Supermaven offers a 30-day free trial of the Pro tier ($10/month), providing full access to 1M token context window, largest model, style adaptation, and $5/month chat credits. No credit card is required to start the trial (implied), and trial conversion to paid is automatic after 30 days unless cancelled. Trial terms and auto-renewal policy are not explicitly detailed.
Unique: 30-day free trial of Pro tier with full feature access (1M context, largest model, chat credits), versus competitors (Copilot 2-month free trial, Tabnine free tier only) with different trial lengths and feature access. Supermaven's approach is generous but with undisclosed auto-renewal terms.
vs alternatives: Full Pro feature access during trial compared to limited free tier; trade-off is undisclosed auto-renewal policy and potential unexpected charges if not cancelled.
Supermaven requires internet connectivity and server-side inference; no offline mode or local inference capability is mentioned or available. All code completion requests are sent to Supermaven's backend servers for processing, and responses are returned over the network. This creates a hard dependency on network connectivity and Supermaven's service availability; if the service is down or network is unavailable, code completion is not available.
Unique: Supermaven has no offline mode or local inference capability; all processing is server-side. GitHub Copilot also requires server-side inference, but Tabnine offers local inference options for some use cases. Supermaven's lack of offline capability is a significant limitation for developers with connectivity constraints.
vs alternatives: Supermaven's server-side-only approach is comparable to GitHub Copilot; Tabnine offers local inference options, making Tabnine more suitable for offline work. Supermaven's lack of offline capability is a weakness vs. Tabnine.
Analyzes recent code edits and inferred coding patterns to adapt inline suggestions to match team conventions, naming patterns, and structural preferences. The mechanism is implicit (not explicit fine-tuning) and operates only on Pro/Team tiers, suggesting pattern learning from editor activity rather than explicit configuration. Free tier uses a single base model without personalization.
Unique: Implicit style adaptation via editor activity analysis without explicit configuration, versus competitors (Copilot, Tabnine) that require manual style guides or explicit fine-tuning. Supermaven's approach is transparent to the user but also non-configurable and undisclosed in mechanism.
vs alternatives: Requires no manual style configuration compared to tools requiring explicit style guides; trade-off is lack of transparency and inability to control or export learned styles.
Delivers code suggestions to the editor inline as the developer types, with a claimed baseline latency of 250ms from keystroke to suggestion display. The system uses a cloud inference backend and local editor plugin to minimize round-trip time. Latency claim is positioned against an unnamed competitor (783ms), but methodology is undisclosed and no independent verification is provided.
Unique: Claimed 250ms latency via optimized cloud inference pipeline and editor plugin architecture, versus competitors with higher latency (783ms unnamed baseline). Actual differentiation is undisclosed; mechanism may involve request batching, model quantization, or edge caching, but specifics are not public.
vs alternatives: Faster than unnamed competitor (250ms vs 783ms claimed); trade-off is cloud dependency and unverified latency claim with no SLA or performance guarantee.
Provides native editor extensions for VS Code, JetBrains IDEs (IntelliJ IDEA, PyCharm, WebStorm, etc.), and Neovim, enabling inline suggestion rendering, hotkey-driven chat access, and compiler diagnostic integration directly within the editor. Each plugin variant is maintained separately and integrates with the editor's native autocomplete UI, keybinding system, and file context APIs.
Unique: Native plugins for three major editor ecosystems (VS Code, JetBrains, Neovim) with integrated chat and diff application, versus competitors (Copilot, Tabnine) that support broader editor ecosystems but with less deep integration in some cases. Supermaven's approach prioritizes depth over breadth.
vs alternatives: Deep integration with VS Code and JetBrains (native autocomplete UI, hotkey system) compared to web-based tools or lighter integrations; trade-off is limited editor support (no Sublime, Vim, Emacs) and undisclosed Neovim support details.
+5 more capabilities