Skip to main content
Glama

Taskive

by ai.taskive.mcp
OverviewDiscussionsAdmin

Server Details

AI-native project management plus a persistent memory & knowledge layer for agents: live tasks, sprints, AI risk scores, burnout signals, project memory, decision logs, and semantic knowledge search — 100+ tools via OAuth 2.1, free plan.

Glama couldn't complete the latest health check. If this server requires authentication, missing or expired test credentials may be the cause. A test profile lets Glama authenticate for health checks and discover tools; it is separate from your personal connections.

If you are the author, claim ownership, then add or update a test profile under Admin → Test Profile.

Status
Unhealthy
OAuth
Works in Glama
Last Tested
Transport
Streamable HTTP
URL

TDQS

C2.6/5.0

Scored across 98 tools

Disambiguation3/5

Many tools target distinct resources (tasks, projects, sprints, epics, comments, workflows, context entries), so overall disambiguation is decent. However, there are a few overlapping pairs (e.g., add_task_blocker vs add_task_dependency, log_decision vs write_context) and many similar-looking AI/narrative endpoints that could confuse an agent.

Naming Consistency4/5

The naming convention is predominantly verb_noun in snake_case (e.g., create_task, list_projects, delete_comment). There are minor deviations like get_my_burnout, get_start_task_context, and test_ai_connection, but the overall pattern is clear and predictable.

Tool Count1/5

With 98 tools, the surface is extremely bloated for a project management API. Many endpoints are rarely needed (e.g., separate AI dashboard generate and refine, multiple risk scoring triggers, several context entry endpoints). This volume makes tool selection difficult and suggests poor scoping.

Completeness3/5

The server covers core project management operations (CRUD for tasks, projects, sprints, epics, comments, workflows) plus AI features and a knowledge store. However, notable gaps exist: team management is read-only (only list_teams_mcp), and admin features are sparse. The extensive AI-related tools feel over-engineered compared to the basics.

Tool Schema Changelog

Recent tool additions, removals, and schema changes observed during successful MCP inspections.

  1. 98 tool updates
    • First observedadd_project_member
    • First observedadd_task_blocker
    • First observedadd_task_dependency
    • First observedai_health
    • First observedarchive_project
    • First observedbulk_assign
    • First observedcomplete_sprint
    • First observedcreate_comment
    • First observedcreate_epic
    • First observedcreate_field_schema
    • First observedcreate_project
    • First observedcreate_sprint
    • First observedcreate_task
    • First observedcreate_workflow_state
    • First observedcreate_workflow_transition
    • First observeddelete_comment
    • First observeddelete_context_entry
    • First observeddelete_epic
    • First observeddelete_field_schema
    • First observeddelete_org_ai_config
    • First observeddelete_project
    • First observeddelete_sprint
    • First observeddelete_task
    • First observeddelete_workflow_state
    • First observeddelete_workflow_transition
    • First observedduplicate_task
    • First observedextract_tasks
    • First observedextract_tasks_upload
    • First observedfull_text_search
    • First observedgenerate_dashboard
    • First observedget_ai_usage_summary
    • First observedget_board
    • First observedget_board_summary
    • First observedget_context_entry
    • First observedget_epic
    • First observedget_focus_mode
    • First observedget_my_burnout
    • First observedget_my_identity
    • First observedget_org_ai_config
    • First observedget_pending_labels
    • First observedget_project
    • First observedget_project_briefs
    • First observedget_project_memory
    • First observedget_project_velocity_trend
    • First observedget_sprint
    • First observedget_sprint_burndown
    • First observedget_sprint_report
    • First observedget_start_task_context
    • First observedget_suggestions
    • First observedget_task
    • First observedget_task_risk
    • First observedget_team_burnout
    • First observedget_velocity_trend
    • First observedlist_assignable_members
    • First observedlist_comments
    • First observedlist_context_entries
    • First observedlist_epics
    • First observedlist_field_schemas
    • First observedlist_my_tasks
    • First observedlist_project_members
    • First observedlist_projects
    • First observedlist_sprints
    • First observedlist_task_activity
    • First observedlist_task_blocked_by
    • First observedlist_task_blockers
    • First observedlist_task_field_values
    • First observedlist_tasks
    • First observedlist_teams_mcp
    • First observedlist_workflow_states
    • First observedlist_workflow_transitions
    • First observedlog_decision
    • First observedmove_task
    • First observedput_org_ai_config
    • First observedrecompute_burnout
    • First observedrefine_dashboard
    • First observedremove_project_member
    • First observedremove_task_blocker
    • First observedremove_task_dependency
    • First observedreorder_backlog_task
    • First observedrestore_project
    • First observedsave_session_summary
    • First observedsearch_context
    • First observedset_task_field_value
    • First observedstart_sprint
    • First observedsuggest_assignment
    • First observedtest_ai_connection
    • First observedtrigger_board_risk_score
    • First observedtrigger_task_risk_score
    • First observedupdate_agile_settings
    • First observedupdate_context_entry
    • First observedupdate_epic
    • First observedupdate_project_settings
    • First observedupdate_sprint
    • First observedupdate_task
    • First observedupdate_task_state
    • First observedupdate_workflow_state
    • First observedupdate_workflow_transition
    • First observedwrite_context

Related MCP Servers

  • Citesurf MCP

    citesurf
    A
    license
    A
    quality
    C
    maintenance
    Enables brand visibility monitoring across major AI platforms like ChatGPT, Claude, Gemini, and Perplexity. It allows users to track visibility scores, analyze competitor data, and receive actionable insights to improve AI-generated brand recommendations.
    16
    9 npm
    1
    MIT

  • CompetitorPulse

    vk-ai
    A
    license
    Not graded
    quality
    B
    maintenance
    Enables tracking competitor websites, changelogs, blog feeds, and pricing pages with meaningful diffs, classification, and Markdown digests via MCP tools for listing, adding, removing competitors, running checks, and retrieving digests or changes.
    MIT
  • industrylens-mcp by IndustryLensOp

    industrylens-mcpofficial

    IndustryLensOp
    A
    license
    Not graded
    quality
    B
    maintenance
    Browse IndustryLens's published competitive-intelligence reports and head-to-head competitor comparisons from any AI agent — real, source-backed data.
    MIT
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources