Gittensory MCP connects Claude and other MCP clients to private, metadata-only Gittensor contribution mining workflows for branch preflight, scoreability estimates, maintainer-fit checks, and public-safe PR packets.
Run Gittensory against the repository and branch you intend to analyze; the MCP is designed for branch preflight, maintainer-fit checks, and PR packet preparation, not broad autonomous code changes., Treat scoreability and risk-adjusted priority as estimates only. They are not payout, reward, acceptance, or merge guarantees., Review generated PR packet text before publishing it. Public output should stay maintainer-friendly and must not leak private scoreability, risk, or reward framing., Prefer local stdio for normal agent use. The remote MCP endpoint is useful for cloud agents, but it shifts more workflow state through the hosted API.
Privacy notes
Gittensory documents metadata-only analysis by default: source contents are not uploaded during the normal MCP branch analysis flow., Authentication uses GitHub OAuth Device Flow and Gittensory session tokens; the MCP does not ask users to paste or store GitHub personal access tokens., Branch metadata, GitHub identity, repository context, linked issues, labels, validation summaries, and preflight blockers may be sent to Gittensory API surfaces as part of analysis., Avoid pasting secrets, wallet material, hotkeys, private source, or unpublished reviewability details into prompts or public PR output.
Author
JSONbored
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-03
Decision playbook
Review trust signals before you adopt
Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.
Compare context
Selected
0
Current score
78
Baseline
—
Delta
No baseline selected
No major trust-signal divergence detected in the current selection.
Source and provenance checks
Complete
Confirm ownership and provenance before trusting install instructions.
Source link availableRequired
Open the canonical repository and verify ownership.
Done
Source provenance statusRequired
Marked as source-backed.
Done
Metadata reviewed
Registry metadata indicates a reviewed listing.
Done
Safety and privacy checks
Complete
Validate risk disclosures before installation or API wiring.
Safety notes presentRequired
Review the listed safety guidance before running commands.
Done
Privacy notes presentRequired
Review data handling notes before connecting accounts or secrets.
Done
Trust level risk gateRequired
Trust level does not block evaluation.
Done
Package and install checks
Needs review
Check package metadata and artifact integrity signals.
Install payload available
Install or copy payload is available for review.
Done
Package verification flag
No package verification flag provided.
Pending
Checksum metadata
No checksum provided for downloaded artifact.
Pending
Compare-driven decision checks
Needs review
Use compare context to validate trade-offs before adoption.
Compare tray has multiple entries
Add at least one more entry to compare trust differences.
Current risk score 16/100. Use staged verification before broader rollout.
Risk 16
Pre-adoption checks
Validate source and review signals before any execution.
Confirm source provenanceRequired
Source URL/provenance metadata is present.
Done
Confirm metadata review state
Listing has review metadata.
Done
Verify install payload
Install/config payload exists and can be inspected.
Done
Security checks
Confirm safety, privacy, and package integrity signals.
Review safety notesRequired
Safety notes are present.
Done
Review privacy notesRequired
Privacy notes are present.
Done
Verify package integrity metadata
No package verification/checksum metadata.
Pending
Rollout
Adopt in controlled steps based on the selected plan.
Run in isolated sandbox firstRequired
Use a constrained sandbox and observe behavior across multiple tasks.
Pending
Roll out graduallyRequired
Roll out to a small cohort before wider usage.
Pending
Set monitoring and fallback
Define rollback path and monitor errors after adoption.
Pending
Evidence readiness
Evidence readiness matrix · balanced
Required evidence gates are covered (5/6 signals complete).
Risk 15
Source provenance
Present
Source repository/provenance is listed.
Required in this preset
Metadata review
Present
Review metadata is present.
Required in this preset
Safety notes
Present
Safety notes are present.
Required in this preset
Privacy notes
Present
Privacy notes are present.
Optional in this preset
Package integrity
Missing
Package integrity metadata is missing.
Optional in this preset
Install payload
Present
Install payload is available.
Required in this preset
Required evidence gates are covered for this preset.
Decision timeline
Decision timeline · balanced
5/6 steps complete with no blocking gaps for this preset.
Risk 14
triage
Confirm source provenanceRequired
Source/provenance metadata is available.
Done
triage
Check metadata review statusRequired
Review metadata is available.
Done
verify
Review safety notesRequired
Safety notes are available.
Done
verify
Review privacy notes
Privacy notes are available.
Done
verify
Validate package integrity metadata
Package integrity metadata is missing.
Pending
rollout
Verify install payload and commandsRequired
Install payload is available.
Done
No required blockers for this timeline preset.
Prerequisite readiness
Prerequisite readiness
4 prerequisites to line up before setup. Have accounts and credentials ready first.
0/4 ready
Account & credentials2Install & runtime25 minutes
Safety & privacy surface
Safety & privacy surface
4 safety and 4 privacy notes across 5 risk areas. Review closely: credentials & tokens, network access, third-party handling.
5 areas
SafetyExecution & processesRun Gittensory against the repository and branch you intend to analyze; the MCP is designed for branch preflight, maintainer-fit checks, and PR packet preparation, not broad autonomous code changes.
SafetyGeneralTreat scoreability and risk-adjusted priority as estimates only. They are not payout, reward, acceptance, or merge guarantees.
SafetyGeneralReview generated PR packet text before publishing it. Public output should stay maintainer-friendly and must not leak private scoreability, risk, or reward framing.
SafetyNetwork accessPrefer local stdio for normal agent use. The remote MCP endpoint is useful for cloud agents, but it shifts more workflow state through the hosted API.
PrivacyNetwork accessGittensory documents metadata-only analysis by default: source contents are not uploaded during the normal MCP branch analysis flow.
PrivacyCredentials & tokensAuthentication uses GitHub OAuth Device Flow and Gittensory session tokens; the MCP does not ask users to paste or store GitHub personal access tokens.
PrivacyThird-party handlingBranch metadata, GitHub identity, repository context, linked issues, labels, validation summaries, and preflight blockers may be sent to Gittensory API surfaces as part of analysis.
PrivacyCredentials & tokensAvoid pasting secrets, wallet material, hotkeys, private source, or unpublished reviewability details into prompts or public PR output.
Safety notes
Run Gittensory against the repository and branch you intend to analyze; the MCP is designed for branch preflight, maintainer-fit checks, and PR packet preparation, not broad autonomous code changes.
Treat scoreability and risk-adjusted priority as estimates only. They are not payout, reward, acceptance, or merge guarantees.
Review generated PR packet text before publishing it. Public output should stay maintainer-friendly and must not leak private scoreability, risk, or reward framing.
Prefer local stdio for normal agent use. The remote MCP endpoint is useful for cloud agents, but it shifts more workflow state through the hosted API.
Privacy notes
Gittensory documents metadata-only analysis by default: source contents are not uploaded during the normal MCP branch analysis flow.
Authentication uses GitHub OAuth Device Flow and Gittensory session tokens; the MCP does not ask users to paste or store GitHub personal access tokens.
Branch metadata, GitHub identity, repository context, linked issues, labels, validation summaries, and preflight blockers may be sent to Gittensory API surfaces as part of analysis.
Avoid pasting secrets, wallet material, hotkeys, private source, or unpublished reviewability details into prompts or public PR output.
Prerequisites
Node.js and npx available (verify with: npx --version)
Claude Code, Claude Desktop, Codex, Cursor, or another MCP-capable client
GitHub account access for the OAuth Device Flow login
Network access to the Gittensory API when using login, preflight, or remote MCP
Gittensory MCP gives Claude and other MCP-capable coding agents a private
control surface for Gittensor OSS contribution workflows. It focuses on the
work that happens before a contributor opens or updates a PR: branch metadata
analysis, preflight blockers, maintainer-fit context, scoreability estimates,
queue pressure, duplicate risk, and public-safe PR packet drafting.
The server is published as @jsonbored/gittensory-mcp and is designed to run
locally over stdio by default. Gittensory also exposes a remote MCP endpoint for
cloud-hosted agents, but the local stdio path is the recommended starting point
because it keeps the client process, GitHub Device Flow login, and local branch
context on the user's machine.
Gittensory is built for the Gittensor ecosystem, but it is not an official
subnet frontend and does not provide reward guarantees. Its scoreability
language is private MCP/API context for planning and reviewability; users should
treat those values as estimates and follow current Gittensor rules for any
eligibility or rewards.
Features
Local stdio MCP server for Claude, Codex, Cursor, and other MCP clients.
Config generators for Codex, Claude Desktop, Cursor, and generic MCP clients.
GitHub OAuth Device Flow login without asking for a GitHub personal access
token.
Metadata-only branch analysis for refs, changed-file metadata, linked issues,
labels, commit messages, and validation summaries.
Preflight checks for branch blockers, account blockers, queue pressure, lane
fit, duplicate risk, and maintainer friction.
Private scoreability estimates for current gated state, clean-gate scenarios,
pending merges, linked issue state, and best reasonable case.
Public-safe PR packet drafting that avoids private score, reward, and risk
language in maintainer-facing GitHub output.
Remote MCP endpoint for cloud agents that cannot run a local Node process.
Use Cases
Ask Claude to check whether a Gittensor contribution branch is ready before
opening a PR.
Generate a maintainer-friendly PR packet without exposing private
scoreability or reward language.
Inspect blockers such as stale upstream, missing issue links, crowded lanes,
queue pressure, or branch hygiene problems.
Compare potential contribution lanes before spending time on a low-fit or
duplicate PR.
Give maintainers an on-demand reviewability packet for confirmed miner PRs
while keeping public GitHub comments quiet and sanitized.
Installation
Claude Code
Confirm npx is available: npx --version.
Add the MCP server:
claude mcp add gittensory -- npx -y @jsonbored/gittensory-mcp@latest --stdio
Restart or refresh Claude Code's MCP session.
Ask Claude to run a lightweight Gittensory status or doctor check.
Claude Desktop
Open claude_desktop_config.json.
Add the gittensory server to mcpServers.
Restart Claude Desktop.
Run gittensory-mcp login when the server asks for GitHub authentication.
Create maintainer-facing PR text that avoids private scoreability and reward
claims.
gittensory-mcp agent packet --json
Security
Gittensory's normal MCP analysis path is metadata-only by default; do not
paste source code, credentials, wallet material, or private maintainer notes
into prompts unless you intend to expose them to your active agent context.
The CLI uses GitHub OAuth Device Flow and Gittensory session tokens, not raw
GitHub personal access token prompts.
Scoreability values are private estimates for planning and prioritization.
They should not be copied into public GitHub comments, PR descriptions, or
maintainer replies.
Generated PR packets should be reviewed before use, especially when a repo has
strict contribution, issue-linking, or disclosure rules.
Troubleshooting
npx cannot resolve the package
Confirm Node.js and npm are installed, then retry with the explicit package
name: npx -y @jsonbored/gittensory-mcp@latest --help.
Authentication does not complete
Run gittensory-mcp login again and complete the GitHub Device Flow in the
browser. Then verify the session with gittensory-mcp whoami.
Claude cannot see the MCP server
Check that the config uses the npx command and includes
@jsonbored/gittensory-mcp@latest plus --stdio. Restart the MCP client after
editing configuration.
The branch analysis looks stale
Fetch the target repository, confirm the active branch is the branch you want to
analyze, and rerun gittensory-mcp analyze-branch --login your-login --json.
Show that Gittensory MCP Server for Claude is listed on HeyClaude. Paste this Markdown into your README — it renders the badge and links back to this page.
[](https://heyclau.de/entry/mcp/gittensory-mcp)
How it compares
Gittensory MCP Server for Claude side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.
2 trust signals differ across this comparison (Source provenance, Submitter).
Gittensory MCP connects Claude and other MCP clients to private, metadata-only Gittensor contribution mining workflows for branch preflight, scoreability estimates, maintainer-fit checks, and public-safe PR packets.
Connect Claude to Algolia-managed MCP servers for curated public search and recommendation access or internal, user-scoped search and analytics workflows.
Official Baselight remote MCP server for searching and querying a catalog of 70,000+ public datasets from Claude via OAuth or x-api-key authentication.
✓Run Gittensory against the repository and branch you intend to analyze; the MCP is designed for branch preflight, maintainer-fit checks, and PR packet preparation, not broad autonomous code changes.
Treat scoreability and risk-adjusted priority as estimates only. They are not payout, reward, acceptance, or merge guarantees.
Review generated PR packet text before publishing it. Public output should stay maintainer-friendly and must not leak private scoreability, risk, or reward framing.
Prefer local stdio for normal agent use. The remote MCP endpoint is useful for cloud agents, but it shifts more workflow state through the hosted API.
✓Algolia documents two Algolia-managed MCP offerings. Public MCP is for curated search and recommendation access to selected indices; Productivity MCP is for internal, user-scoped workflows that inherit the signed-in user's Algolia permissions.
Algolia describes Public MCP as a beta feature under its Beta Services terms. Treat setup behavior, limits, dashboard controls, and client support as changeable until Algolia marks the feature generally available.
Public MCP uses a generated server URL for a specific Algolia application and selected indices. Do not publish that URL in public repositories, issues, logs, screenshots, or client configs unless the exposed records are intended for that audience.
Public MCP client configuration does not require client-side authentication, so the selected Search API key restrictions, selected indices, Recommend models, and index descriptions are the primary controls.
Productivity MCP is documented as read-only for analysis and exploration, but it can expose anything the signed-in user can access in Algolia. Use a least-privilege account for sensitive projects.
Algolia says MCP usage counts toward the existing Algolia plan. Monitor API usage and avoid broad automated loops, high-traffic prompts, or repeated large searches through an MCP client.
✓Query tools may return large result sets; scope filters to avoid excessive data transfer.
Some datasets are community-contributed; validate schema and quality before production use.
OAuth tokens and API keys grant persistent catalog access until revoked.
Do not run unreviewed SQL-like queries against sensitive production mirrors without safeguards.
✓This server sends web searches, URLs, scraping targets, browser actions, package names, and dataset requests to Bright Data APIs.
Review website terms, robots policies, rate limits, jurisdictional requirements, and internal scraping policies before automating collection.
`PRO_MODE`, browser automation groups, data-product groups, and batch tools can increase cost, request volume, and operational impact.
The server can create or use Bright Data zones through API calls; review account permissions and zone settings before running it with broad API tokens.
Use `RATE_LIMIT`, group selection, and explicit tool allowlists to keep agent-driven browsing and scraping bounded.
Privacy notes
✓Gittensory documents metadata-only analysis by default: source contents are not uploaded during the normal MCP branch analysis flow.
Authentication uses GitHub OAuth Device Flow and Gittensory session tokens; the MCP does not ask users to paste or store GitHub personal access tokens.
Branch metadata, GitHub identity, repository context, linked issues, labels, validation summaries, and preflight blockers may be sent to Gittensory API surfaces as part of analysis.
Avoid pasting secrets, wallet material, hotkeys, private source, or unpublished reviewability details into prompts or public PR output.
✓Algolia MCP can return search hits, object attributes, facet values, recommendations, index names, analytics metrics, top searches, no-result queries, countries, click positions, user counts, and other search performance data into the model conversation.
Public MCP exposes records according to the configured indices and Search API key permissions. Remove private object attributes or use secured, filtered, or separate indices before connecting customer-facing agents.
Productivity MCP uses the signed-in user's Algolia identity and permissions. Treat prompts, outputs, screenshots, and MCP client logs as internal data whenever they include Algolia analytics, index names, or object records.
Do not paste Admin API keys, write API keys, private secured API keys, customer identifiers, unreleased product catalog fields, pricing rules, personal data, or raw exports into prompts or PR comments.
Algolia recommends prompt guidance that preserves result fidelity. Avoid asking the assistant to filter, reorder, or summarize returned hits when an exact search result order matters.
✓Search terms and query filters are sent to Baselight and may appear in usage logs.
Dataset rows returned through MCP may include PII or licensed third-party content subject to dataset terms.
Avoid pasting raw dataset excerpts containing personal data into public channels.
✓Bright Data API tokens must stay in environment variables or secret managers and should never be committed to MCP configuration files.
Queries, URLs, package names, web pages, scraping outputs, dataset filters, and browser activity may be visible to Bright Data, the MCP client, and the model provider.
Public web data can still contain personal data, copyrighted content, customer information, or contractual restrictions.
Tool outputs can include scraped page text, search results, social or ecommerce dataset fields, package metadata, and browser screenshots depending on enabled tools.
Prerequisites
Node.js and npx available (verify with: npx --version)
Claude Code, Claude Desktop, Codex, Cursor, or another MCP-capable client
GitHub account access for the OAuth Device Flow login
Network access to the Gittensory API when using login, preflight, or remote MCP
Algolia account with access to the applications and indices you want Claude to use.
MCP-capable client with remote HTTP transport support, such as Claude, Claude Code, ChatGPT, Cursor, VS Code, Gemini CLI, Codex, OpenAI Playground, or another compatible client.
For Algolia Productivity MCP, access to enable Productivity MCP in the Algolia dashboard and sign in through the MCP client when prompted.
For Algolia Public MCP, an Algolia application with at least one index and the dashboard permission to create or copy a Public MCP server URL.
Baselight account with API access or OAuth authorisation for dataset queries.
Claude Pro, Team, or Enterprise with Connectors support, or another MCP client with remote HTTP connectors.
Understanding of the dataset topics you plan to query to narrow catalog searches effectively.
Compliance review if exported dataset rows may contain regulated or personal data.
Node.js and npx available to the MCP client runtime.
Bright Data account and API token stored as `API_TOKEN`.
Review of Bright Data plan limits, free-tier scope, paid modes, and data-product terms.
A decision about whether to use default rapid tools, `PRO_MODE`, `GROUPS`, or explicit `TOOLS`.
Install
claude mcp add gittensory -- npx -y @jsonbored/gittensory-mcp@latest --stdio
claude mcp add --transport http algolia https://mcp.algolia.com/mcp
claude mcp add --transport http baselight https://api.baselight.app/mcp